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authorNavan Chauhan <navanchauhan@gmail.com>2020-01-19 13:11:50 +0530
committerNavan Chauhan <navanchauhan@gmail.com>2020-01-19 13:11:50 +0530
commitf324a12da007a9f39eb718d23e7349fad4e6f870 (patch)
tree07e9d087dc94b29118d21a5b6c3d0d4a6d3b2c8f
parent955d2a062b340dd41ab7daf377d240425660761e (diff)
Publish deploy 2020-01-19 13:11
-rw-r--r--Themes/styles.css5
-rw-r--r--assets/posts/kaggle-colab/ss1.pngbin0 -> 151575 bytes
-rw-r--r--assets/posts/kaggle-colab/ss2.pngbin0 -> 43899 bytes
-rw-r--r--assets/posts/kaggle-colab/ss3.pngbin0 -> 54283 bytes
-rw-r--r--assets/posts/kaggle-colab/ss4.pngbin0 -> 14510 bytes
-rw-r--r--feed.rss222
-rw-r--r--index.html2
-rw-r--r--posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab/index.html9
-rw-r--r--posts/2020-01-16-Image-Classifier-Using-Turicreate/index.html213
-rw-r--r--posts/index.html2
-rw-r--r--sitemap.xml2
-rw-r--r--styles.css5
-rw-r--r--tags/colab/index.html2
-rw-r--r--tags/index.html2
-rw-r--r--tags/kaggle/index.html1
-rw-r--r--tags/turicreate/index.html2
-rw-r--r--tags/tutorial/index.html2
17 files changed, 459 insertions, 10 deletions
diff --git a/Themes/styles.css b/Themes/styles.css
index afc641a..5328b36 100644
--- a/Themes/styles.css
+++ b/Themes/styles.css
@@ -186,6 +186,8 @@ a {
img {
max-width: 100%;
+ margin-bottom: 1em;
+ margin-top: 1em;
width: auto\9;
height: auto;
vertical-align: middle;
@@ -205,7 +207,8 @@ pre {
display: block;
background-color: #fdf6e3;
color: #586e75;
-
+ margin-bottom: 1em;
+ margin-top: 1em;
border-radius: 4px;
}
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index 0da058c..b55ce6f 100644
--- a/feed.rss
+++ b/feed.rss
@@ -1,4 +1,224 @@
-<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content"><channel><title>Navan Chauhan</title><description>Welcome to my personal fragment of the internet.</description><link>https://navanchauhan.github.io/</link><language>en</language><lastBuildDate>Sat, 18 Jan 2020 19:19:50 +0530</lastBuildDate><pubDate>Sat, 18 Jan 2020 19:19:50 +0530</pubDate><ttl>250</ttl><atom:link href="https://navanchauhan.github.io/feed.rss" rel="self" type="application/rss+xml"/><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2020-01-14-Converting-between-PIL-NumPy</guid><title>Converting between image and NumPy array</title><description>Short code snippet for converting between PIL image and NumPy arrays.</description><link>https://navanchauhan.github.io/posts/2020-01-14-Converting-between-PIL-NumPy</link><pubDate>Tue, 14 Jan 2020 00:10:00 +0530</pubDate><content:encoded><![CDATA[<h1>Converting between image and NumPy array</h1><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">numpy</span>
+<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content"><channel><title>Navan Chauhan</title><description>Welcome to my personal fragment of the internet.</description><link>https://navanchauhan.github.io/</link><language>en</language><lastBuildDate>Sun, 19 Jan 2020 13:11:26 +0530</lastBuildDate><pubDate>Sun, 19 Jan 2020 13:11:26 +0530</pubDate><ttl>250</ttl><atom:link href="https://navanchauhan.github.io/feed.rss" rel="self" type="application/rss+xml"/><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2020-01-16-Image-Classifier-Using-Turicreate</guid><title>Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire</title><description>Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle</description><link>https://navanchauhan.github.io/posts/2020-01-16-Image-Classifier-Using-Turicreate</link><pubDate>Thu, 16 Jan 2020 10:36:00 +0530</pubDate><content:encoded><![CDATA[<h1>Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire</h1><p><em>For setting up Kaggle with Google Colab, please refer to <a href="https://navanchauhan.github.io//posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab/"> my previous post</a></em></p><h2>Dataset</h2><h3>Mounting Google Drive</h3><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">os</span>
+<span class="kn">from</span> <span class="nn">google.colab</span> <span class="kn">import</span> <span class="n">drive</span>
+<span class="n">drive</span><span class="o">.</span><span class="n">mount</span><span class="p">(</span><span class="s1">&#39;/content/drive&#39;</span><span class="p">)</span>
+</div>
+
+</code></pre><h3>Downloading Dataset from Kaggle</h3><pre><code><div class="highlight"><span></span><span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s1">&#39;KAGGLE_CONFIG_DIR&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;/content/drive/My Drive/&quot;</span>
+<span class="err">!</span><span class="n">kaggle</span> <span class="n">datasets</span> <span class="n">download</span> <span class="n">ashutosh69</span><span class="o">/</span><span class="n">fire</span><span class="o">-</span><span class="ow">and</span><span class="o">-</span><span class="n">smoke</span><span class="o">-</span><span class="n">dataset</span>
+<span class="err">!</span><span class="n">unzip</span> <span class="s2">&quot;fire-and-smoke-dataset.zip&quot;</span>
+</div>
+
+</code></pre><h2>Pre-Processing</h2><pre><code><div class="highlight"><span></span><span class="nt">!mkdir</span><span class="na"> default smoke fire</span>
+</div>
+
+</code></pre><p><br></p><pre><code><div class="highlight"><span></span><span class="nt">!ls</span><span class="na"> data/data/img_data/train/default/*.jpg</span>
+</div>
+
+</code></pre><p><br></p><pre><code><div class="highlight"><span></span><span class="nt">img_1002.jpg</span><span class="na"> img_20.jpg img_519.jpg img_604.jpg img_80.jpg</span>
+<span class="na">img_1003.jpg img_21.jpg img_51.jpg img_60.jpg img_8.jpg</span>
+<span class="na">img_1007.jpg img_22.jpg img_520.jpg img_61.jpg img_900.jpg</span>
+<span class="na">img_100.jpg img_23.jpg img_521.jpg &#39;img_62 (2).jpg&#39; img_920.jpg</span>
+<span class="na">img_1014.jpg img_24.jpg &#39;img_52 (2).jpg&#39; img_62.jpg img_921.jpg</span>
+<span class="na">img_1018.jpg img_29.jpg img_522.jpg &#39;img_63 (2).jpg&#39; img_922.jpg</span>
+<span class="na">img_101.jpg img_3000.jpg img_523.jpg img_63.jpg img_923.jpg</span>
+<span class="na">img_1027.jpg img_335.jpg img_524.jpg img_66.jpg img_924.jpg</span>
+<span class="na">img_102.jpg img_336.jpg img_52.jpg img_67.jpg img_925.jpg</span>
+<span class="na">img_1042.jpg img_337.jpg img_530.jpg img_68.jpg img_926.jpg</span>
+<span class="na">img_1043.jpg img_338.jpg img_531.jpg img_700.jpg img_927.jpg</span>
+<span class="na">img_1046.jpg img_339.jpg &#39;img_53 (2).jpg&#39; img_701.jpg img_928.jpg</span>
+<span class="na">img_1052.jpg img_340.jpg img_532.jpg img_702.jpg img_929.jpg</span>
+<span class="na">img_107.jpg img_341.jpg img_533.jpg img_703.jpg img_930.jpg</span>
+<span class="na">img_108.jpg img_3.jpg img_537.jpg img_704.jpg img_931.jpg</span>
+<span class="na">img_109.jpg img_400.jpg img_538.jpg img_705.jpg img_932.jpg</span>
+<span class="na">img_10.jpg img_471.jpg img_539.jpg img_706.jpg img_933.jpg</span>
+<span class="na">img_118.jpg img_472.jpg img_53.jpg img_707.jpg img_934.jpg</span>
+<span class="na">img_12.jpg img_473.jpg img_540.jpg img_708.jpg img_935.jpg</span>
+<span class="na">img_14.jpg img_488.jpg img_541.jpg img_709.jpg img_938.jpg</span>
+<span class="na">img_15.jpg img_489.jpg &#39;img_54 (2).jpg&#39; img_70.jpg img_958.jpg</span>
+<span class="na">img_16.jpg img_490.jpg img_542.jpg img_710.jpg img_971.jpg</span>
+<span class="na">img_17.jpg img_491.jpg img_543.jpg &#39;img_71 (2).jpg&#39; img_972.jpg</span>
+<span class="na">img_18.jpg img_492.jpg img_54.jpg img_71.jpg img_973.jpg</span>
+<span class="na">img_19.jpg img_493.jpg &#39;img_55 (2).jpg&#39; img_72.jpg img_974.jpg</span>
+<span class="na">img_1.jpg img_494.jpg img_55.jpg img_73.jpg img_975.jpg</span>
+<span class="na">img_200.jpg img_495.jpg img_56.jpg img_74.jpg img_980.jpg</span>
+<span class="na">img_201.jpg img_496.jpg img_57.jpg img_75.jpg img_988.jpg</span>
+<span class="na">img_202.jpg img_497.jpg img_58.jpg img_76.jpg img_9.jpg</span>
+<span class="na">img_203.jpg img_4.jpg img_59.jpg img_77.jpg</span>
+<span class="na">img_204.jpg img_501.jpg img_601.jpg img_78.jpg</span>
+<span class="na">img_205.jpg img_502.jpg img_602.jpg img_79.jpg</span>
+<span class="na">img_206.jpg img_50.jpg img_603.jpg img_7.jpg</span>
+</div>
+
+</code></pre><p>The image files are not actually JPEG, thus we first need to save them in the correct format for Turicreate</p><pre><code><div class="highlight"><span></span><span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span>
+<span class="kn">import</span> <span class="nn">glob</span>
+
+
+<span class="n">folders</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;default&quot;</span><span class="p">,</span><span class="s2">&quot;smoke&quot;</span><span class="p">,</span><span class="s2">&quot;fire&quot;</span><span class="p">]</span>
+<span class="k">for</span> <span class="n">folder</span> <span class="ow">in</span> <span class="n">folders</span><span class="p">:</span>
+ <span class="n">n</span> <span class="o">=</span> <span class="mi">1</span>
+ <span class="k">for</span> <span class="nb">file</span> <span class="ow">in</span> <span class="n">glob</span><span class="o">.</span><span class="n">glob</span><span class="p">(</span><span class="s2">&quot;./data/data/img_data/train/&quot;</span> <span class="o">+</span> <span class="n">folder</span> <span class="o">+</span> <span class="s2">&quot;/*.jpg&quot;</span><span class="p">):</span>
+ <span class="n">im</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="nb">file</span><span class="p">)</span>
+ <span class="n">rgb_im</span> <span class="o">=</span> <span class="n">im</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s1">&#39;RGB&#39;</span><span class="p">)</span>
+ <span class="n">rgb_im</span><span class="o">.</span><span class="n">save</span><span class="p">((</span><span class="n">folder</span> <span class="o">+</span> <span class="s2">&quot;/&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">n</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot;.jpg&quot;</span><span class="p">),</span> <span class="n">quality</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span>
+ <span class="n">n</span> <span class="o">+=</span><span class="mi">1</span>
+ <span class="k">for</span> <span class="nb">file</span> <span class="ow">in</span> <span class="n">glob</span><span class="o">.</span><span class="n">glob</span><span class="p">(</span><span class="s2">&quot;./data/data/img_data/train/&quot;</span> <span class="o">+</span> <span class="n">folder</span> <span class="o">+</span> <span class="s2">&quot;/*.jpg&quot;</span><span class="p">):</span>
+ <span class="n">im</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="nb">file</span><span class="p">)</span>
+ <span class="n">rgb_im</span> <span class="o">=</span> <span class="n">im</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s1">&#39;RGB&#39;</span><span class="p">)</span>
+ <span class="n">rgb_im</span><span class="o">.</span><span class="n">save</span><span class="p">((</span><span class="n">folder</span> <span class="o">+</span> <span class="s2">&quot;/&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">n</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot;.jpg&quot;</span><span class="p">),</span> <span class="n">quality</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span>
+ <span class="n">n</span> <span class="o">+=</span><span class="mi">1</span>
+</div>
+
+</code></pre><p><br></p><pre><code><div class="highlight"><span></span><span class="nt">!mkdir</span><span class="na"> train</span>
+<span class="na">!mv default ./train</span>
+<span class="na">!mv smoke ./train</span>
+<span class="na">!mv fire ./train</span>
+</div>
+
+</code></pre><h2>Making the Image Classifier</h2><h3>Making an SFrame</h3><pre><code><div class="highlight"><span></span><span class="nt">!pip</span><span class="na"> install turicreate</span>
+</div>
+
+</code></pre><p><br></p><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">turicreate</span> <span class="kn">as</span> <span class="nn">tc</span>
+<span class="kn">import</span> <span class="nn">os</span>
+
+<span class="n">data</span> <span class="o">=</span> <span class="n">tc</span><span class="o">.</span><span class="n">image_analysis</span><span class="o">.</span><span class="n">load_images</span><span class="p">(</span><span class="s2">&quot;./train&quot;</span><span class="p">,</span> <span class="n">with_path</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
+
+<span class="n">data</span><span class="p">[</span><span class="s2">&quot;label&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="s2">&quot;path&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">path</span><span class="p">:</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">basename</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">dirname</span><span class="p">(</span><span class="n">path</span><span class="p">)))</span>
+
+<span class="k">print</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
+
+<span class="n">data</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="s1">&#39;fire-smoke.sframe&#39;</span><span class="p">)</span>
+</div>
+
+</code></pre><p><br></p><pre><code><div class="highlight"><span></span><span class="nt">+-------------------------+------------------------+</span>
+<span class="err">| path | image |</span>
+<span class="nt">+-------------------------+------------------------+</span>
+<span class="err">| ./train/default/1.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/10.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/100.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/101.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/102.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/103.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/104.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/105.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/106.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/107.jpg | Height: 224 Width: 224 |</span>
+<span class="nt">+-------------------------+------------------------+</span>
+<span class="nt">[2028</span><span class="na"> rows x 2 columns]</span>
+<span class="na">Note</span><span class="p">:</span><span class="err"> </span><span class="nc">Only</span><span class="err"> </span><span class="nc">the</span><span class="err"> </span><span class="nc">head</span><span class="err"> </span><span class="nc">of</span><span class="err"> </span><span class="nc">the</span><span class="err"> </span><span class="nc">SFrame</span><span class="err"> </span><span class="nc">is</span><span class="err"> </span><span class="nc">printed.</span>
+<span class="nt">You</span><span class="na"> can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.</span>
+<span class="na">+-------------------------+------------------------+---------+</span>
+<span class="p">|</span><span class="na"> path </span><span class="p">|</span><span class="na"> image </span><span class="p">|</span><span class="na"> label </span><span class="p">|</span>
+<span class="nt">+-------------------------+------------------------+---------+</span>
+<span class="err">| ./train/default/1.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/10.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/100.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/101.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/102.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/103.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/104.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/105.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/106.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/107.jpg | Height: 224 Width: 224 | default |</span>
+<span class="nt">+-------------------------+------------------------+---------+</span>
+<span class="nt">[2028</span><span class="na"> rows x 3 columns]</span>
+<span class="na">Note</span><span class="p">:</span><span class="err"> </span><span class="nc">Only</span><span class="err"> </span><span class="nc">the</span><span class="err"> </span><span class="nc">head</span><span class="err"> </span><span class="nc">of</span><span class="err"> </span><span class="nc">the</span><span class="err"> </span><span class="nc">SFrame</span><span class="err"> </span><span class="nc">is</span><span class="err"> </span><span class="nc">printed.</span>
+<span class="nt">You</span><span class="na"> can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.</span>
+</div>
+
+</code></pre><h3>Making the Model</h3><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">turicreate</span> <span class="kn">as</span> <span class="nn">tc</span>
+
+<span class="c1"># Load the data</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">tc</span><span class="o">.</span><span class="n">SFrame</span><span class="p">(</span><span class="s1">&#39;fire-smoke.sframe&#39;</span><span class="p">)</span>
+
+<span class="c1"># Make a train-test split</span>
+<span class="n">train_data</span><span class="p">,</span> <span class="n">test_data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">random_split</span><span class="p">(</span><span class="mf">0.8</span><span class="p">)</span>
+
+<span class="c1"># Create the model</span>
+<span class="n">model</span> <span class="o">=</span> <span class="n">tc</span><span class="o">.</span><span class="n">image_classifier</span><span class="o">.</span><span class="n">create</span><span class="p">(</span><span class="n">train_data</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="s1">&#39;label&#39;</span><span class="p">)</span>
+
+<span class="c1"># Save predictions to an SArray</span>
+<span class="n">predictions</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test_data</span><span class="p">)</span>
+
+<span class="c1"># Evaluate the model and print the results</span>
+<span class="n">metrics</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">test_data</span><span class="p">)</span>
+<span class="k">print</span><span class="p">(</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;accuracy&#39;</span><span class="p">])</span>
+
+<span class="c1"># Save the model for later use in Turi Create</span>
+<span class="n">model</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="s1">&#39;fire-smoke.model&#39;</span><span class="p">)</span>
+
+<span class="c1"># Export for use in Core ML</span>
+<span class="n">model</span><span class="o">.</span><span class="n">export_coreml</span><span class="p">(</span><span class="s1">&#39;fire-smoke.mlmodel&#39;</span><span class="p">)</span>
+</div>
+
+</code></pre><p><br></p><pre><code><div class="highlight"><span></span><span class="nt">Performing</span><span class="na"> feature extraction on resized images...</span>
+<span class="na">Completed 64/1633</span>
+<span class="na">Completed 128/1633</span>
+<span class="na">Completed 192/1633</span>
+<span class="na">Completed 256/1633</span>
+<span class="na">Completed 320/1633</span>
+<span class="na">Completed 384/1633</span>
+<span class="na">Completed 448/1633</span>
+<span class="na">Completed 512/1633</span>
+<span class="na">Completed 576/1633</span>
+<span class="na">Completed 640/1633</span>
+<span class="na">Completed 704/1633</span>
+<span class="na">Completed 768/1633</span>
+<span class="na">Completed 832/1633</span>
+<span class="na">Completed 896/1633</span>
+<span class="na">Completed 960/1633</span>
+<span class="na">Completed 1024/1633</span>
+<span class="na">Completed 1088/1633</span>
+<span class="na">Completed 1152/1633</span>
+<span class="na">Completed 1216/1633</span>
+<span class="na">Completed 1280/1633</span>
+<span class="na">Completed 1344/1633</span>
+<span class="na">Completed 1408/1633</span>
+<span class="na">Completed 1472/1633</span>
+<span class="na">Completed 1536/1633</span>
+<span class="na">Completed 1600/1633</span>
+<span class="na">Completed 1633/1633</span>
+<span class="na">PROGRESS</span><span class="p">:</span><span class="err"> </span><span class="nc">Creating</span><span class="err"> </span><span class="nc">a</span><span class="err"> </span><span class="nc">validation</span><span class="err"> </span><span class="nc">set</span><span class="err"> </span><span class="nc">from</span><span class="err"> </span><span class="nc">5</span><span class="err"> </span><span class="nc">percent</span><span class="err"> </span><span class="nc">of</span><span class="err"> </span><span class="nc">training</span><span class="err"> </span><span class="nc">data.</span><span class="err"> </span><span class="nc">This</span><span class="err"> </span><span class="nc">may</span><span class="err"> </span><span class="nc">take</span><span class="err"> </span><span class="nc">a</span><span class="err"> </span><span class="nc">while.</span>
+ <span class="err">You can set ``validation_set=None`` to disable validation tracking.</span>
+
+<span class="nt">Logistic</span><span class="na"> regression</span><span class="p">:</span>
+<span class="nt">--------------------------------------------------------</span>
+<span class="nt">Number</span><span class="na"> of examples </span><span class="p">:</span><span class="err"> </span><span class="nc">1551</span>
+<span class="nt">Number</span><span class="na"> of classes </span><span class="p">:</span><span class="err"> </span><span class="nc">3</span>
+<span class="nt">Number</span><span class="na"> of feature columns </span><span class="p">:</span><span class="err"> </span><span class="nc">1</span>
+<span class="nt">Number</span><span class="na"> of unpacked features </span><span class="p">:</span><span class="err"> </span><span class="nc">2048</span>
+<span class="nt">Number</span><span class="na"> of coefficients </span><span class="p">:</span><span class="err"> </span><span class="nc">4098</span>
+<span class="nt">Starting</span><span class="na"> L-BFGS</span>
+<span class="na">--------------------------------------------------------</span>
+<span class="na">+-----------+----------+-----------+--------------+-------------------+---------------------+</span>
+<span class="p">|</span><span class="na"> Iteration </span><span class="p">|</span><span class="na"> Passes </span><span class="p">|</span><span class="na"> Step size </span><span class="p">|</span><span class="na"> Elapsed Time </span><span class="p">|</span><span class="na"> Training Accuracy </span><span class="p">|</span><span class="na"> Validation Accuracy </span><span class="p">|</span>
+<span class="nt">+-----------+----------+-----------+--------------+-------------------+---------------------+</span>
+<span class="err">| 0 | 6 | 0.018611 | 0.891830 | 0.553836 | 0.560976 |</span>
+<span class="err">| 1 | 10 | 0.390832 | 1.622383 | 0.744681 | 0.792683 |</span>
+<span class="err">| 2 | 11 | 0.488541 | 1.943987 | 0.733075 | 0.804878 |</span>
+<span class="err">| 3 | 14 | 2.442703 | 2.512545 | 0.727917 | 0.841463 |</span>
+<span class="err">| 4 | 15 | 2.442703 | 2.826964 | 0.861380 | 0.853659 |</span>
+<span class="err">| 9 | 28 | 2.340435 | 5.492035 | 0.941328 | 0.975610 |</span>
+<span class="nt">+-----------+----------+-----------+--------------+-------------------+---------------------+</span>
+<span class="nt">Performing</span><span class="na"> feature extraction on resized images...</span>
+<span class="na">Completed 64/395</span>
+<span class="na">Completed 128/395</span>
+<span class="na">Completed 192/395</span>
+<span class="na">Completed 256/395</span>
+<span class="na">Completed 320/395</span>
+<span class="na">Completed 384/395</span>
+<span class="na">Completed 395/395</span>
+<span class="na">0.9316455696202531</span>
+</div>
+
+</code></pre><p>We just got an accuracy of 94% on Training Data and 97% on Validation Data!</p>]]></content:encoded></item><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab</guid><title>Setting up Kaggle to use with Google Colab</title><description>Tutorial on setting up kaggle, to use with Google Colab</description><link>https://navanchauhan.github.io/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab</link><pubDate>Wed, 15 Jan 2020 23:36:00 +0530</pubDate><content:encoded><![CDATA[<h1>Setting up Kaggle to use with Google Colab</h1><p><em>In order to be able to access Kaggle Datasets, you will need to have an account on Kaggle (which is Free)</em></p><h2>Grabbing Our Tokens</h2><h3>Go to Kaggle</h3><img src="https://navanchauhan.github.io//assets/posts/kaggle-colab/ss1.png" alt=""Homepage""/><h3>Click on your User Profile and Click on My Account</h3><img src="https://navanchauhan.github.io//assets/posts/kaggle-colab/ss2.png" alt=""Account""/><h3>Scroll Down untill you see Create New API Token</h3><img src="https://navanchauhan.github.io//assets/posts/kaggle-colab/ss3.png"/><h3>This will download your token as a JSON file</h3><img src="https://navanchauhan.github.io//assets/posts/kaggle-colab/ss4.png"/><p>Copy the File to the root folder of your Google Drive</p><h2>Setting up Colab</h2><h3>Mounting Google Drive</h3><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">os</span>
+<span class="kn">from</span> <span class="nn">google.colab</span> <span class="kn">import</span> <span class="n">drive</span>
+<span class="n">drive</span><span class="o">.</span><span class="n">mount</span><span class="p">(</span><span class="s1">&#39;/content/drive&#39;</span><span class="p">)</span>
+</div>
+
+</code></pre><p>After this click on the URL in the output section, login and then paste the Auth Code</p><h3>Configuring Kaggle</h3><pre><code><div class="highlight"><span></span><span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s1">&#39;KAGGLE_CONFIG_DIR&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;/content/drive/My Drive/&quot;</span>
+</div>
+
+</code></pre><p>Voila! You can now download kaggel datasets</p>]]></content:encoded></item><item><guid isPermaLink="true">https://navanchauhan.github.io/posts/2020-01-14-Converting-between-PIL-NumPy</guid><title>Converting between image and NumPy array</title><description>Short code snippet for converting between PIL image and NumPy arrays.</description><link>https://navanchauhan.github.io/posts/2020-01-14-Converting-between-PIL-NumPy</link><pubDate>Tue, 14 Jan 2020 00:10:00 +0530</pubDate><content:encoded><![CDATA[<h1>Converting between image and NumPy array</h1><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">numpy</span>
<span class="kn">import</span> <span class="nn">PIL</span>
<span class="c1"># Convert PIL Image to NumPy array</span>
diff --git a/index.html b/index.html
index 17e5bbf..8d8bd43 100644
--- a/index.html
+++ b/index.html
@@ -1 +1 @@
-<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/"/><meta name="twitter:url" content="https://navanchauhan.github.io/"/><meta name="og:url" content="https://navanchauhan.github.io/"/><title>Hi! | Navan Chauhan</title><meta name="twitter:title" content="Hi! | Navan Chauhan"/><meta name="og:title" content="Hi! | Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><h1>Hi!</h1><p class="description">Welcome to my personal fragment of the internet.</p><h2>Latest content</h2><ul class="item-list"><li><article><h1><a href="/posts/2020-01-14-Converting-between-PIL-NumPy">Converting between image and NumPy array</a></h1><ul class="tag-list"><li><a href="/tags/codesnippet">code-snippet</a></li><li><a href="/tags/tutorial">tutorial</a></li></ul><span>🕑 0 minute read.</span><p>Short code snippet for converting between PIL image and NumPy arrays.</p></article></li><li><article><h1><a href="/posts/2019-12-22-Fake-News-Detector">Building a Fake News Detector with Turicreate</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/swiftui">swiftUI</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>In this tutorial we will build a fake news detecting app from scratch, using Turicreate for the machine learning model and SwiftUI for building the app</p></article></li><li><article><h1><a href="/posts/2019-12-16-TensorFlow-Polynomial-Regression">Polynomial Regression Using TensorFlow</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 16 minute read.</span><p>Polynomial regression using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-10-TensorFlow-Model-Prediction">Making Predictions using Image Classifier (TensorFlow)</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/codesnippet">code-snippet</a></li></ul><span>🕑 1 minute read.</span><p>Making predictions for image classification models built using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-08-Image-Classifier-Tensorflow">Creating a Custom Image Classifier using Tensorflow 2.x and Keras for Detecting Malaria</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 4 minute read.</span><p>Tutorial on creating an image classifier model using TensorFlow which detects malaria</p></article></li><li><article><h1><a href="/posts/2019-12-08-Splitting-Zips">Splitting ZIPs into Multiple Parts</a></h1><ul class="tag-list"><li><a href="/tags/codesnippet">code-snippet</a></li><li><a href="/tags/tutorial">tutorial</a></li></ul><span>🕑 0 minute read.</span><p>Short code snippet for splitting zips.</p></article></li><li><article><h1><a href="/publications/2019-05-14-Detecting-Driver-Fatigue-Over-Speeding-and-Speeding-up-Post-Accident-Response">Detecting Driver Fatigue, Over-Speeding, and Speeding up Post-Accident Response</a></h1><ul class="tag-list"><li><a href="/tags/publication">publication</a></li></ul><span>🕑 1 minute read.</span><p>This paper is about Detecting Driver Fatigue, Over-Speeding, and Speeding up Post-Accident Response.</p></article></li><li><article><h1><a href="/posts/hello-world">Hello World</a></h1><ul class="tag-list"><li><a href="/tags/helloworld">hello-world</a></li><li><a href="/tags/article">article</a></li></ul><span>🕑 0 minute read.</span><p>My first post.</p></article></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
+<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/"/><meta name="twitter:url" content="https://navanchauhan.github.io/"/><meta name="og:url" content="https://navanchauhan.github.io/"/><title>Hi! | Navan Chauhan</title><meta name="twitter:title" content="Hi! | Navan Chauhan"/><meta name="og:title" content="Hi! | Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><h1>Hi!</h1><p class="description">Welcome to my personal fragment of the internet.</p><h2>Latest content</h2><ul class="item-list"><li><article><h1><a href="/posts/2020-01-16-Image-Classifier-Using-Turicreate">Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle</p></article></li><li><article><h1><a href="/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab">Setting up Kaggle to use with Google Colab</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li><li><a href="/tags/kaggle">kaggle</a></li></ul><span>🕑 1 minute read.</span><p>Tutorial on setting up kaggle, to use with Google Colab</p></article></li><li><article><h1><a href="/posts/2020-01-14-Converting-between-PIL-NumPy">Converting between image and NumPy array</a></h1><ul class="tag-list"><li><a href="/tags/codesnippet">code-snippet</a></li><li><a href="/tags/tutorial">tutorial</a></li></ul><span>🕑 0 minute read.</span><p>Short code snippet for converting between PIL image and NumPy arrays.</p></article></li><li><article><h1><a href="/posts/2019-12-22-Fake-News-Detector">Building a Fake News Detector with Turicreate</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/swiftui">swiftUI</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>In this tutorial we will build a fake news detecting app from scratch, using Turicreate for the machine learning model and SwiftUI for building the app</p></article></li><li><article><h1><a href="/posts/2019-12-16-TensorFlow-Polynomial-Regression">Polynomial Regression Using TensorFlow</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 16 minute read.</span><p>Polynomial regression using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-10-TensorFlow-Model-Prediction">Making Predictions using Image Classifier (TensorFlow)</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/codesnippet">code-snippet</a></li></ul><span>🕑 1 minute read.</span><p>Making predictions for image classification models built using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-08-Image-Classifier-Tensorflow">Creating a Custom Image Classifier using Tensorflow 2.x and Keras for Detecting Malaria</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 4 minute read.</span><p>Tutorial on creating an image classifier model using TensorFlow which detects malaria</p></article></li><li><article><h1><a href="/posts/2019-12-08-Splitting-Zips">Splitting ZIPs into Multiple Parts</a></h1><ul class="tag-list"><li><a href="/tags/codesnippet">code-snippet</a></li><li><a href="/tags/tutorial">tutorial</a></li></ul><span>🕑 0 minute read.</span><p>Short code snippet for splitting zips.</p></article></li><li><article><h1><a href="/publications/2019-05-14-Detecting-Driver-Fatigue-Over-Speeding-and-Speeding-up-Post-Accident-Response">Detecting Driver Fatigue, Over-Speeding, and Speeding up Post-Accident Response</a></h1><ul class="tag-list"><li><a href="/tags/publication">publication</a></li></ul><span>🕑 1 minute read.</span><p>This paper is about Detecting Driver Fatigue, Over-Speeding, and Speeding up Post-Accident Response.</p></article></li><li><article><h1><a href="/posts/hello-world">Hello World</a></h1><ul class="tag-list"><li><a href="/tags/helloworld">hello-world</a></li><li><a href="/tags/article">article</a></li></ul><span>🕑 0 minute read.</span><p>My first post.</p></article></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
diff --git a/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab/index.html b/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab/index.html
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--- /dev/null
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@@ -0,0 +1,9 @@
+<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab"/><meta name="twitter:url" content="https://navanchauhan.github.io/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab"/><meta name="og:url" content="https://navanchauhan.github.io/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab"/><title>Setting up Kaggle to use with Google Colab | Navan Chauhan</title><meta name="twitter:title" content="Setting up Kaggle to use with Google Colab | Navan Chauhan"/><meta name="og:title" content="Setting up Kaggle to use with Google Colab | Navan Chauhan"/><meta name="description" content="Tutorial on setting up kaggle, to use with Google Colab"/><meta name="twitter:description" content="Tutorial on setting up kaggle, to use with Google Colab"/><meta name="og:description" content="Tutorial on setting up kaggle, to use with Google Colab"/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body class="item-page"><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a class="selected" href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><article><div class="content"><span class="reading-time">🕑 1 minute read.</span><h1>Setting up Kaggle to use with Google Colab</h1><p><em>In order to be able to access Kaggle Datasets, you will need to have an account on Kaggle (which is Free)</em></p><h2>Grabbing Our Tokens</h2><h3>Go to Kaggle</h3><img src="/assets/posts/kaggle-colab/ss1.png" alt=""Homepage""/><h3>Click on your User Profile and Click on My Account</h3><img src="/assets/posts/kaggle-colab/ss2.png" alt=""Account""/><h3>Scroll Down untill you see Create New API Token</h3><img src="/assets/posts/kaggle-colab/ss3.png"/><h3>This will download your token as a JSON file</h3><img src="/assets/posts/kaggle-colab/ss4.png"/><p>Copy the File to the root folder of your Google Drive</p><h2>Setting up Colab</h2><h3>Mounting Google Drive</h3><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">os</span>
+<span class="kn">from</span> <span class="nn">google.colab</span> <span class="kn">import</span> <span class="n">drive</span>
+<span class="n">drive</span><span class="o">.</span><span class="n">mount</span><span class="p">(</span><span class="s1">&#39;/content/drive&#39;</span><span class="p">)</span>
+</div>
+
+</code></pre><p>After this click on the URL in the output section, login and then paste the Auth Code</p><h3>Configuring Kaggle</h3><pre><code><div class="highlight"><span></span><span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s1">&#39;KAGGLE_CONFIG_DIR&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;/content/drive/My Drive/&quot;</span>
+</div>
+
+</code></pre><p>Voila! You can now download kaggel datasets</p></div><span>Tagged with: </span><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li><li><a href="/tags/kaggle">kaggle</a></li></ul></article></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
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+<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/posts/2020-01-16-Image-Classifier-Using-Turicreate"/><meta name="twitter:url" content="https://navanchauhan.github.io/posts/2020-01-16-Image-Classifier-Using-Turicreate"/><meta name="og:url" content="https://navanchauhan.github.io/posts/2020-01-16-Image-Classifier-Using-Turicreate"/><title>Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire | Navan Chauhan</title><meta name="twitter:title" content="Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire | Navan Chauhan"/><meta name="og:title" content="Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire | Navan Chauhan"/><meta name="description" content="Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle"/><meta name="twitter:description" content="Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle"/><meta name="og:description" content="Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle"/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body class="item-page"><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a class="selected" href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><article><div class="content"><span class="reading-time">🕑 6 minute read.</span><h1>Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire</h1><p><em>For setting up Kaggle with Google Colab, please refer to <a href="/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab/"> my previous post</a></em></p><h2>Dataset</h2><h3>Mounting Google Drive</h3><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">os</span>
+<span class="kn">from</span> <span class="nn">google.colab</span> <span class="kn">import</span> <span class="n">drive</span>
+<span class="n">drive</span><span class="o">.</span><span class="n">mount</span><span class="p">(</span><span class="s1">&#39;/content/drive&#39;</span><span class="p">)</span>
+</div>
+
+</code></pre><h3>Downloading Dataset from Kaggle</h3><pre><code><div class="highlight"><span></span><span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s1">&#39;KAGGLE_CONFIG_DIR&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;/content/drive/My Drive/&quot;</span>
+<span class="err">!</span><span class="n">kaggle</span> <span class="n">datasets</span> <span class="n">download</span> <span class="n">ashutosh69</span><span class="o">/</span><span class="n">fire</span><span class="o">-</span><span class="ow">and</span><span class="o">-</span><span class="n">smoke</span><span class="o">-</span><span class="n">dataset</span>
+<span class="err">!</span><span class="n">unzip</span> <span class="s2">&quot;fire-and-smoke-dataset.zip&quot;</span>
+</div>
+
+</code></pre><h2>Pre-Processing</h2><pre><code><div class="highlight"><span></span><span class="nt">!mkdir</span><span class="na"> default smoke fire</span>
+</div>
+
+</code></pre><p><br></p><pre><code><div class="highlight"><span></span><span class="nt">!ls</span><span class="na"> data/data/img_data/train/default/*.jpg</span>
+</div>
+
+</code></pre><p><br></p><pre><code><div class="highlight"><span></span><span class="nt">img_1002.jpg</span><span class="na"> img_20.jpg img_519.jpg img_604.jpg img_80.jpg</span>
+<span class="na">img_1003.jpg img_21.jpg img_51.jpg img_60.jpg img_8.jpg</span>
+<span class="na">img_1007.jpg img_22.jpg img_520.jpg img_61.jpg img_900.jpg</span>
+<span class="na">img_100.jpg img_23.jpg img_521.jpg &#39;img_62 (2).jpg&#39; img_920.jpg</span>
+<span class="na">img_1014.jpg img_24.jpg &#39;img_52 (2).jpg&#39; img_62.jpg img_921.jpg</span>
+<span class="na">img_1018.jpg img_29.jpg img_522.jpg &#39;img_63 (2).jpg&#39; img_922.jpg</span>
+<span class="na">img_101.jpg img_3000.jpg img_523.jpg img_63.jpg img_923.jpg</span>
+<span class="na">img_1027.jpg img_335.jpg img_524.jpg img_66.jpg img_924.jpg</span>
+<span class="na">img_102.jpg img_336.jpg img_52.jpg img_67.jpg img_925.jpg</span>
+<span class="na">img_1042.jpg img_337.jpg img_530.jpg img_68.jpg img_926.jpg</span>
+<span class="na">img_1043.jpg img_338.jpg img_531.jpg img_700.jpg img_927.jpg</span>
+<span class="na">img_1046.jpg img_339.jpg &#39;img_53 (2).jpg&#39; img_701.jpg img_928.jpg</span>
+<span class="na">img_1052.jpg img_340.jpg img_532.jpg img_702.jpg img_929.jpg</span>
+<span class="na">img_107.jpg img_341.jpg img_533.jpg img_703.jpg img_930.jpg</span>
+<span class="na">img_108.jpg img_3.jpg img_537.jpg img_704.jpg img_931.jpg</span>
+<span class="na">img_109.jpg img_400.jpg img_538.jpg img_705.jpg img_932.jpg</span>
+<span class="na">img_10.jpg img_471.jpg img_539.jpg img_706.jpg img_933.jpg</span>
+<span class="na">img_118.jpg img_472.jpg img_53.jpg img_707.jpg img_934.jpg</span>
+<span class="na">img_12.jpg img_473.jpg img_540.jpg img_708.jpg img_935.jpg</span>
+<span class="na">img_14.jpg img_488.jpg img_541.jpg img_709.jpg img_938.jpg</span>
+<span class="na">img_15.jpg img_489.jpg &#39;img_54 (2).jpg&#39; img_70.jpg img_958.jpg</span>
+<span class="na">img_16.jpg img_490.jpg img_542.jpg img_710.jpg img_971.jpg</span>
+<span class="na">img_17.jpg img_491.jpg img_543.jpg &#39;img_71 (2).jpg&#39; img_972.jpg</span>
+<span class="na">img_18.jpg img_492.jpg img_54.jpg img_71.jpg img_973.jpg</span>
+<span class="na">img_19.jpg img_493.jpg &#39;img_55 (2).jpg&#39; img_72.jpg img_974.jpg</span>
+<span class="na">img_1.jpg img_494.jpg img_55.jpg img_73.jpg img_975.jpg</span>
+<span class="na">img_200.jpg img_495.jpg img_56.jpg img_74.jpg img_980.jpg</span>
+<span class="na">img_201.jpg img_496.jpg img_57.jpg img_75.jpg img_988.jpg</span>
+<span class="na">img_202.jpg img_497.jpg img_58.jpg img_76.jpg img_9.jpg</span>
+<span class="na">img_203.jpg img_4.jpg img_59.jpg img_77.jpg</span>
+<span class="na">img_204.jpg img_501.jpg img_601.jpg img_78.jpg</span>
+<span class="na">img_205.jpg img_502.jpg img_602.jpg img_79.jpg</span>
+<span class="na">img_206.jpg img_50.jpg img_603.jpg img_7.jpg</span>
+</div>
+
+</code></pre><p>The image files are not actually JPEG, thus we first need to save them in the correct format for Turicreate</p><pre><code><div class="highlight"><span></span><span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span>
+<span class="kn">import</span> <span class="nn">glob</span>
+
+
+<span class="n">folders</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;default&quot;</span><span class="p">,</span><span class="s2">&quot;smoke&quot;</span><span class="p">,</span><span class="s2">&quot;fire&quot;</span><span class="p">]</span>
+<span class="k">for</span> <span class="n">folder</span> <span class="ow">in</span> <span class="n">folders</span><span class="p">:</span>
+ <span class="n">n</span> <span class="o">=</span> <span class="mi">1</span>
+ <span class="k">for</span> <span class="nb">file</span> <span class="ow">in</span> <span class="n">glob</span><span class="o">.</span><span class="n">glob</span><span class="p">(</span><span class="s2">&quot;./data/data/img_data/train/&quot;</span> <span class="o">+</span> <span class="n">folder</span> <span class="o">+</span> <span class="s2">&quot;/*.jpg&quot;</span><span class="p">):</span>
+ <span class="n">im</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="nb">file</span><span class="p">)</span>
+ <span class="n">rgb_im</span> <span class="o">=</span> <span class="n">im</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s1">&#39;RGB&#39;</span><span class="p">)</span>
+ <span class="n">rgb_im</span><span class="o">.</span><span class="n">save</span><span class="p">((</span><span class="n">folder</span> <span class="o">+</span> <span class="s2">&quot;/&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">n</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot;.jpg&quot;</span><span class="p">),</span> <span class="n">quality</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span>
+ <span class="n">n</span> <span class="o">+=</span><span class="mi">1</span>
+ <span class="k">for</span> <span class="nb">file</span> <span class="ow">in</span> <span class="n">glob</span><span class="o">.</span><span class="n">glob</span><span class="p">(</span><span class="s2">&quot;./data/data/img_data/train/&quot;</span> <span class="o">+</span> <span class="n">folder</span> <span class="o">+</span> <span class="s2">&quot;/*.jpg&quot;</span><span class="p">):</span>
+ <span class="n">im</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="nb">file</span><span class="p">)</span>
+ <span class="n">rgb_im</span> <span class="o">=</span> <span class="n">im</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s1">&#39;RGB&#39;</span><span class="p">)</span>
+ <span class="n">rgb_im</span><span class="o">.</span><span class="n">save</span><span class="p">((</span><span class="n">folder</span> <span class="o">+</span> <span class="s2">&quot;/&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">n</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot;.jpg&quot;</span><span class="p">),</span> <span class="n">quality</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span>
+ <span class="n">n</span> <span class="o">+=</span><span class="mi">1</span>
+</div>
+
+</code></pre><p><br></p><pre><code><div class="highlight"><span></span><span class="nt">!mkdir</span><span class="na"> train</span>
+<span class="na">!mv default ./train</span>
+<span class="na">!mv smoke ./train</span>
+<span class="na">!mv fire ./train</span>
+</div>
+
+</code></pre><h2>Making the Image Classifier</h2><h3>Making an SFrame</h3><pre><code><div class="highlight"><span></span><span class="nt">!pip</span><span class="na"> install turicreate</span>
+</div>
+
+</code></pre><p><br></p><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">turicreate</span> <span class="kn">as</span> <span class="nn">tc</span>
+<span class="kn">import</span> <span class="nn">os</span>
+
+<span class="n">data</span> <span class="o">=</span> <span class="n">tc</span><span class="o">.</span><span class="n">image_analysis</span><span class="o">.</span><span class="n">load_images</span><span class="p">(</span><span class="s2">&quot;./train&quot;</span><span class="p">,</span> <span class="n">with_path</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
+
+<span class="n">data</span><span class="p">[</span><span class="s2">&quot;label&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="s2">&quot;path&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">path</span><span class="p">:</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">basename</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">dirname</span><span class="p">(</span><span class="n">path</span><span class="p">)))</span>
+
+<span class="k">print</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
+
+<span class="n">data</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="s1">&#39;fire-smoke.sframe&#39;</span><span class="p">)</span>
+</div>
+
+</code></pre><p><br></p><pre><code><div class="highlight"><span></span><span class="nt">+-------------------------+------------------------+</span>
+<span class="err">| path | image |</span>
+<span class="nt">+-------------------------+------------------------+</span>
+<span class="err">| ./train/default/1.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/10.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/100.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/101.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/102.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/103.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/104.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/105.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/106.jpg | Height: 224 Width: 224 |</span>
+<span class="err">| ./train/default/107.jpg | Height: 224 Width: 224 |</span>
+<span class="nt">+-------------------------+------------------------+</span>
+<span class="nt">[2028</span><span class="na"> rows x 2 columns]</span>
+<span class="na">Note</span><span class="p">:</span><span class="err"> </span><span class="nc">Only</span><span class="err"> </span><span class="nc">the</span><span class="err"> </span><span class="nc">head</span><span class="err"> </span><span class="nc">of</span><span class="err"> </span><span class="nc">the</span><span class="err"> </span><span class="nc">SFrame</span><span class="err"> </span><span class="nc">is</span><span class="err"> </span><span class="nc">printed.</span>
+<span class="nt">You</span><span class="na"> can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.</span>
+<span class="na">+-------------------------+------------------------+---------+</span>
+<span class="p">|</span><span class="na"> path </span><span class="p">|</span><span class="na"> image </span><span class="p">|</span><span class="na"> label </span><span class="p">|</span>
+<span class="nt">+-------------------------+------------------------+---------+</span>
+<span class="err">| ./train/default/1.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/10.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/100.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/101.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/102.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/103.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/104.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/105.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/106.jpg | Height: 224 Width: 224 | default |</span>
+<span class="err">| ./train/default/107.jpg | Height: 224 Width: 224 | default |</span>
+<span class="nt">+-------------------------+------------------------+---------+</span>
+<span class="nt">[2028</span><span class="na"> rows x 3 columns]</span>
+<span class="na">Note</span><span class="p">:</span><span class="err"> </span><span class="nc">Only</span><span class="err"> </span><span class="nc">the</span><span class="err"> </span><span class="nc">head</span><span class="err"> </span><span class="nc">of</span><span class="err"> </span><span class="nc">the</span><span class="err"> </span><span class="nc">SFrame</span><span class="err"> </span><span class="nc">is</span><span class="err"> </span><span class="nc">printed.</span>
+<span class="nt">You</span><span class="na"> can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.</span>
+</div>
+
+</code></pre><h3>Making the Model</h3><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">turicreate</span> <span class="kn">as</span> <span class="nn">tc</span>
+
+<span class="c1"># Load the data</span>
+<span class="n">data</span> <span class="o">=</span> <span class="n">tc</span><span class="o">.</span><span class="n">SFrame</span><span class="p">(</span><span class="s1">&#39;fire-smoke.sframe&#39;</span><span class="p">)</span>
+
+<span class="c1"># Make a train-test split</span>
+<span class="n">train_data</span><span class="p">,</span> <span class="n">test_data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">random_split</span><span class="p">(</span><span class="mf">0.8</span><span class="p">)</span>
+
+<span class="c1"># Create the model</span>
+<span class="n">model</span> <span class="o">=</span> <span class="n">tc</span><span class="o">.</span><span class="n">image_classifier</span><span class="o">.</span><span class="n">create</span><span class="p">(</span><span class="n">train_data</span><span class="p">,</span> <span class="n">target</span><span class="o">=</span><span class="s1">&#39;label&#39;</span><span class="p">)</span>
+
+<span class="c1"># Save predictions to an SArray</span>
+<span class="n">predictions</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">test_data</span><span class="p">)</span>
+
+<span class="c1"># Evaluate the model and print the results</span>
+<span class="n">metrics</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">evaluate</span><span class="p">(</span><span class="n">test_data</span><span class="p">)</span>
+<span class="k">print</span><span class="p">(</span><span class="n">metrics</span><span class="p">[</span><span class="s1">&#39;accuracy&#39;</span><span class="p">])</span>
+
+<span class="c1"># Save the model for later use in Turi Create</span>
+<span class="n">model</span><span class="o">.</span><span class="n">save</span><span class="p">(</span><span class="s1">&#39;fire-smoke.model&#39;</span><span class="p">)</span>
+
+<span class="c1"># Export for use in Core ML</span>
+<span class="n">model</span><span class="o">.</span><span class="n">export_coreml</span><span class="p">(</span><span class="s1">&#39;fire-smoke.mlmodel&#39;</span><span class="p">)</span>
+</div>
+
+</code></pre><p><br></p><pre><code><div class="highlight"><span></span><span class="nt">Performing</span><span class="na"> feature extraction on resized images...</span>
+<span class="na">Completed 64/1633</span>
+<span class="na">Completed 128/1633</span>
+<span class="na">Completed 192/1633</span>
+<span class="na">Completed 256/1633</span>
+<span class="na">Completed 320/1633</span>
+<span class="na">Completed 384/1633</span>
+<span class="na">Completed 448/1633</span>
+<span class="na">Completed 512/1633</span>
+<span class="na">Completed 576/1633</span>
+<span class="na">Completed 640/1633</span>
+<span class="na">Completed 704/1633</span>
+<span class="na">Completed 768/1633</span>
+<span class="na">Completed 832/1633</span>
+<span class="na">Completed 896/1633</span>
+<span class="na">Completed 960/1633</span>
+<span class="na">Completed 1024/1633</span>
+<span class="na">Completed 1088/1633</span>
+<span class="na">Completed 1152/1633</span>
+<span class="na">Completed 1216/1633</span>
+<span class="na">Completed 1280/1633</span>
+<span class="na">Completed 1344/1633</span>
+<span class="na">Completed 1408/1633</span>
+<span class="na">Completed 1472/1633</span>
+<span class="na">Completed 1536/1633</span>
+<span class="na">Completed 1600/1633</span>
+<span class="na">Completed 1633/1633</span>
+<span class="na">PROGRESS</span><span class="p">:</span><span class="err"> </span><span class="nc">Creating</span><span class="err"> </span><span class="nc">a</span><span class="err"> </span><span class="nc">validation</span><span class="err"> </span><span class="nc">set</span><span class="err"> </span><span class="nc">from</span><span class="err"> </span><span class="nc">5</span><span class="err"> </span><span class="nc">percent</span><span class="err"> </span><span class="nc">of</span><span class="err"> </span><span class="nc">training</span><span class="err"> </span><span class="nc">data.</span><span class="err"> </span><span class="nc">This</span><span class="err"> </span><span class="nc">may</span><span class="err"> </span><span class="nc">take</span><span class="err"> </span><span class="nc">a</span><span class="err"> </span><span class="nc">while.</span>
+ <span class="err">You can set ``validation_set=None`` to disable validation tracking.</span>
+
+<span class="nt">Logistic</span><span class="na"> regression</span><span class="p">:</span>
+<span class="nt">--------------------------------------------------------</span>
+<span class="nt">Number</span><span class="na"> of examples </span><span class="p">:</span><span class="err"> </span><span class="nc">1551</span>
+<span class="nt">Number</span><span class="na"> of classes </span><span class="p">:</span><span class="err"> </span><span class="nc">3</span>
+<span class="nt">Number</span><span class="na"> of feature columns </span><span class="p">:</span><span class="err"> </span><span class="nc">1</span>
+<span class="nt">Number</span><span class="na"> of unpacked features </span><span class="p">:</span><span class="err"> </span><span class="nc">2048</span>
+<span class="nt">Number</span><span class="na"> of coefficients </span><span class="p">:</span><span class="err"> </span><span class="nc">4098</span>
+<span class="nt">Starting</span><span class="na"> L-BFGS</span>
+<span class="na">--------------------------------------------------------</span>
+<span class="na">+-----------+----------+-----------+--------------+-------------------+---------------------+</span>
+<span class="p">|</span><span class="na"> Iteration </span><span class="p">|</span><span class="na"> Passes </span><span class="p">|</span><span class="na"> Step size </span><span class="p">|</span><span class="na"> Elapsed Time </span><span class="p">|</span><span class="na"> Training Accuracy </span><span class="p">|</span><span class="na"> Validation Accuracy </span><span class="p">|</span>
+<span class="nt">+-----------+----------+-----------+--------------+-------------------+---------------------+</span>
+<span class="err">| 0 | 6 | 0.018611 | 0.891830 | 0.553836 | 0.560976 |</span>
+<span class="err">| 1 | 10 | 0.390832 | 1.622383 | 0.744681 | 0.792683 |</span>
+<span class="err">| 2 | 11 | 0.488541 | 1.943987 | 0.733075 | 0.804878 |</span>
+<span class="err">| 3 | 14 | 2.442703 | 2.512545 | 0.727917 | 0.841463 |</span>
+<span class="err">| 4 | 15 | 2.442703 | 2.826964 | 0.861380 | 0.853659 |</span>
+<span class="err">| 9 | 28 | 2.340435 | 5.492035 | 0.941328 | 0.975610 |</span>
+<span class="nt">+-----------+----------+-----------+--------------+-------------------+---------------------+</span>
+<span class="nt">Performing</span><span class="na"> feature extraction on resized images...</span>
+<span class="na">Completed 64/395</span>
+<span class="na">Completed 128/395</span>
+<span class="na">Completed 192/395</span>
+<span class="na">Completed 256/395</span>
+<span class="na">Completed 320/395</span>
+<span class="na">Completed 384/395</span>
+<span class="na">Completed 395/395</span>
+<span class="na">0.9316455696202531</span>
+</div>
+
+</code></pre><p>We just got an accuracy of 94% on Training Data and 97% on Validation Data!</p></div><span>Tagged with: </span><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul></article></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
diff --git a/posts/index.html b/posts/index.html
index c73301f..82fc009 100644
--- a/posts/index.html
+++ b/posts/index.html
@@ -1 +1 @@
-<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/posts"/><meta name="twitter:url" content="https://navanchauhan.github.io/posts"/><meta name="og:url" content="https://navanchauhan.github.io/posts"/><title>Posts | Navan Chauhan</title><meta name="twitter:title" content="Posts | Navan Chauhan"/><meta name="og:title" content="Posts | Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a class="selected" href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><h1>Posts</h1><p>Tips, tricks and tutorials which I think might be useful.</p><ul class="item-list"><li><article><h1><a href="/posts/2019-12-08-Image-Classifier-Tensorflow">Creating a Custom Image Classifier using Tensorflow 2.x and Keras for Detecting Malaria</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 4 minute read.</span><p>Tutorial on creating an image classifier model using TensorFlow which detects malaria</p></article></li><li><article><h1><a href="/posts/2019-12-08-Splitting-Zips">Splitting ZIPs into Multiple Parts</a></h1><ul class="tag-list"><li><a href="/tags/codesnippet">code-snippet</a></li><li><a href="/tags/tutorial">tutorial</a></li></ul><span>🕑 0 minute read.</span><p>Short code snippet for splitting zips.</p></article></li><li><article><h1><a href="/posts/2019-12-10-TensorFlow-Model-Prediction">Making Predictions using Image Classifier (TensorFlow)</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/codesnippet">code-snippet</a></li></ul><span>🕑 1 minute read.</span><p>Making predictions for image classification models built using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-16-TensorFlow-Polynomial-Regression">Polynomial Regression Using TensorFlow</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 16 minute read.</span><p>Polynomial regression using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-22-Fake-News-Detector">Building a Fake News Detector with Turicreate</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/swiftui">swiftUI</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>In this tutorial we will build a fake news detecting app from scratch, using Turicreate for the machine learning model and SwiftUI for building the app</p></article></li><li><article><h1><a href="/posts/2020-01-14-Converting-between-PIL-NumPy">Converting between image and NumPy array</a></h1><ul class="tag-list"><li><a href="/tags/codesnippet">code-snippet</a></li><li><a href="/tags/tutorial">tutorial</a></li></ul><span>🕑 0 minute read.</span><p>Short code snippet for converting between PIL image and NumPy arrays.</p></article></li><li><article><h1><a href="/posts/hello-world">Hello World</a></h1><ul class="tag-list"><li><a href="/tags/helloworld">hello-world</a></li><li><a href="/tags/article">article</a></li></ul><span>🕑 0 minute read.</span><p>My first post.</p></article></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
+<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/posts"/><meta name="twitter:url" content="https://navanchauhan.github.io/posts"/><meta name="og:url" content="https://navanchauhan.github.io/posts"/><title>Posts | Navan Chauhan</title><meta name="twitter:title" content="Posts | Navan Chauhan"/><meta name="og:title" content="Posts | Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a class="selected" href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><h1>Posts</h1><p>Tips, tricks and tutorials which I think might be useful.</p><ul class="item-list"><li><article><h1><a href="/posts/2019-12-08-Image-Classifier-Tensorflow">Creating a Custom Image Classifier using Tensorflow 2.x and Keras for Detecting Malaria</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 4 minute read.</span><p>Tutorial on creating an image classifier model using TensorFlow which detects malaria</p></article></li><li><article><h1><a href="/posts/2019-12-08-Splitting-Zips">Splitting ZIPs into Multiple Parts</a></h1><ul class="tag-list"><li><a href="/tags/codesnippet">code-snippet</a></li><li><a href="/tags/tutorial">tutorial</a></li></ul><span>🕑 0 minute read.</span><p>Short code snippet for splitting zips.</p></article></li><li><article><h1><a href="/posts/2019-12-10-TensorFlow-Model-Prediction">Making Predictions using Image Classifier (TensorFlow)</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/codesnippet">code-snippet</a></li></ul><span>🕑 1 minute read.</span><p>Making predictions for image classification models built using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-16-TensorFlow-Polynomial-Regression">Polynomial Regression Using TensorFlow</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 16 minute read.</span><p>Polynomial regression using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-22-Fake-News-Detector">Building a Fake News Detector with Turicreate</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/swiftui">swiftUI</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>In this tutorial we will build a fake news detecting app from scratch, using Turicreate for the machine learning model and SwiftUI for building the app</p></article></li><li><article><h1><a href="/posts/2020-01-14-Converting-between-PIL-NumPy">Converting between image and NumPy array</a></h1><ul class="tag-list"><li><a href="/tags/codesnippet">code-snippet</a></li><li><a href="/tags/tutorial">tutorial</a></li></ul><span>🕑 0 minute read.</span><p>Short code snippet for converting between PIL image and NumPy arrays.</p></article></li><li><article><h1><a href="/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab">Setting up Kaggle to use with Google Colab</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li><li><a href="/tags/kaggle">kaggle</a></li></ul><span>🕑 1 minute read.</span><p>Tutorial on setting up kaggle, to use with Google Colab</p></article></li><li><article><h1><a href="/posts/2020-01-16-Image-Classifier-Using-Turicreate">Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle</p></article></li><li><article><h1><a href="/posts/hello-world">Hello World</a></h1><ul class="tag-list"><li><a href="/tags/helloworld">hello-world</a></li><li><a href="/tags/article">article</a></li></ul><span>🕑 0 minute read.</span><p>My first post.</p></article></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
diff --git a/sitemap.xml b/sitemap.xml
index dc5fc4e..89ea75a 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -1 +1 @@
-<?xml version="1.0" encoding="UTF-8"?><urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:image="http://www.google.com/schemas/sitemap-image/1.1"><url><loc>https://navanchauhan.github.io/about</loc><changefreq>daily</changefreq><priority>1.0</priority><lastmod>2020-01-14</lastmod></url><url><loc>https://navanchauhan.github.io/posts</loc><changefreq>daily</changefreq><priority>1.0</priority><lastmod>2020-01-14</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2019-12-08-Image-Classifier-Tensorflow</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2019-12-08-Splitting-Zips</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2019-12-10-TensorFlow-Model-Prediction</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2019-12-16-TensorFlow-Polynomial-Regression</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2019-12-22-Fake-News-Detector</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2020-01-14-Converting-between-PIL-NumPy</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url><url><loc>https://navanchauhan.github.io/posts/hello-world</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-04</lastmod></url><url><loc>https://navanchauhan.github.io/publications</loc><changefreq>daily</changefreq><priority>1.0</priority><lastmod>2020-01-14</lastmod></url><url><loc>https://navanchauhan.github.io/publications/2019-05-14-Detecting-Driver-Fatigue-Over-Speeding-and-Speeding-up-Post-Accident-Response</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-04</lastmod></url><url><loc>https://navanchauhan.github.io/tutorials/index</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url></urlset> \ No newline at end of file
+<?xml version="1.0" encoding="UTF-8"?><urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:image="http://www.google.com/schemas/sitemap-image/1.1"><url><loc>https://navanchauhan.github.io/about</loc><changefreq>daily</changefreq><priority>1.0</priority><lastmod>2020-01-14</lastmod></url><url><loc>https://navanchauhan.github.io/posts</loc><changefreq>daily</changefreq><priority>1.0</priority><lastmod>2020-01-16</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2019-12-08-Image-Classifier-Tensorflow</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2019-12-08-Splitting-Zips</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2019-12-10-TensorFlow-Model-Prediction</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2019-12-16-TensorFlow-Polynomial-Regression</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2019-12-22-Fake-News-Detector</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2020-01-14-Converting-between-PIL-NumPy</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-19</lastmod></url><url><loc>https://navanchauhan.github.io/posts/2020-01-16-Image-Classifier-Using-Turicreate</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-19</lastmod></url><url><loc>https://navanchauhan.github.io/posts/hello-world</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-04</lastmod></url><url><loc>https://navanchauhan.github.io/publications</loc><changefreq>daily</changefreq><priority>1.0</priority><lastmod>2020-01-14</lastmod></url><url><loc>https://navanchauhan.github.io/publications/2019-05-14-Detecting-Driver-Fatigue-Over-Speeding-and-Speeding-up-Post-Accident-Response</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-04</lastmod></url><url><loc>https://navanchauhan.github.io/tutorials/index</loc><changefreq>monthly</changefreq><priority>0.5</priority><lastmod>2020-01-18</lastmod></url></urlset> \ No newline at end of file
diff --git a/styles.css b/styles.css
index afc641a..5328b36 100644
--- a/styles.css
+++ b/styles.css
@@ -186,6 +186,8 @@ a {
img {
max-width: 100%;
+ margin-bottom: 1em;
+ margin-top: 1em;
width: auto\9;
height: auto;
vertical-align: middle;
@@ -205,7 +207,8 @@ pre {
display: block;
background-color: #fdf6e3;
color: #586e75;
-
+ margin-bottom: 1em;
+ margin-top: 1em;
border-radius: 4px;
}
diff --git a/tags/colab/index.html b/tags/colab/index.html
index 41e6180..e2ed804 100644
--- a/tags/colab/index.html
+++ b/tags/colab/index.html
@@ -1 +1 @@
-<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/tags/colab"/><meta name="twitter:url" content="https://navanchauhan.github.io/tags/colab"/><meta name="og:url" content="https://navanchauhan.github.io/tags/colab"/><title>Navan Chauhan</title><meta name="twitter:title" content="Navan Chauhan"/><meta name="og:title" content="Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><h1>Tagged with <span class="tag">colab</span></h1><a class="browse-all" href="/tags">Browse all tags</a><ul class="item-list"><li><article><h1><a href="/posts/2019-12-22-Fake-News-Detector">Building a Fake News Detector with Turicreate</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/swiftui">swiftUI</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>In this tutorial we will build a fake news detecting app from scratch, using Turicreate for the machine learning model and SwiftUI for building the app</p></article></li><li><article><h1><a href="/posts/2019-12-16-TensorFlow-Polynomial-Regression">Polynomial Regression Using TensorFlow</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 16 minute read.</span><p>Polynomial regression using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-08-Image-Classifier-Tensorflow">Creating a Custom Image Classifier using Tensorflow 2.x and Keras for Detecting Malaria</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 4 minute read.</span><p>Tutorial on creating an image classifier model using TensorFlow which detects malaria</p></article></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
+<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/tags/colab"/><meta name="twitter:url" content="https://navanchauhan.github.io/tags/colab"/><meta name="og:url" content="https://navanchauhan.github.io/tags/colab"/><title>Navan Chauhan</title><meta name="twitter:title" content="Navan Chauhan"/><meta name="og:title" content="Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><h1>Tagged with <span class="tag">colab</span></h1><a class="browse-all" href="/tags">Browse all tags</a><ul class="item-list"><li><article><h1><a href="/posts/2020-01-16-Image-Classifier-Using-Turicreate">Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle</p></article></li><li><article><h1><a href="/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab">Setting up Kaggle to use with Google Colab</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li><li><a href="/tags/kaggle">kaggle</a></li></ul><span>🕑 1 minute read.</span><p>Tutorial on setting up kaggle, to use with Google Colab</p></article></li><li><article><h1><a href="/posts/2019-12-22-Fake-News-Detector">Building a Fake News Detector with Turicreate</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/swiftui">swiftUI</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>In this tutorial we will build a fake news detecting app from scratch, using Turicreate for the machine learning model and SwiftUI for building the app</p></article></li><li><article><h1><a href="/posts/2019-12-16-TensorFlow-Polynomial-Regression">Polynomial Regression Using TensorFlow</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 16 minute read.</span><p>Polynomial regression using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-08-Image-Classifier-Tensorflow">Creating a Custom Image Classifier using Tensorflow 2.x and Keras for Detecting Malaria</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 4 minute read.</span><p>Tutorial on creating an image classifier model using TensorFlow which detects malaria</p></article></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
diff --git a/tags/index.html b/tags/index.html
index 230748f..d8b001d 100644
--- a/tags/index.html
+++ b/tags/index.html
@@ -1 +1 @@
-<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/tags"/><meta name="twitter:url" content="https://navanchauhan.github.io/tags"/><meta name="og:url" content="https://navanchauhan.github.io/tags"/><title>Navan Chauhan</title><meta name="twitter:title" content="Navan Chauhan"/><meta name="og:title" content="Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><h1>Browse all tags</h1><ul class="all-tags"><li class="tag"><a href="/tags/article">article</a></li><li class="tag"><a href="/tags/codesnippet">code-snippet</a></li><li class="tag"><a href="/tags/colab">colab</a></li><li class="tag"><a href="/tags/helloworld">hello-world</a></li><li class="tag"><a href="/tags/publication">publication</a></li><li class="tag"><a href="/tags/swiftui">swiftUI</a></li><li class="tag"><a href="/tags/tensorflow">tensorflow</a></li><li class="tag"><a href="/tags/turicreate">turicreate</a></li><li class="tag"><a href="/tags/tutorial">tutorial</a></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
+<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/tags"/><meta name="twitter:url" content="https://navanchauhan.github.io/tags"/><meta name="og:url" content="https://navanchauhan.github.io/tags"/><title>Navan Chauhan</title><meta name="twitter:title" content="Navan Chauhan"/><meta name="og:title" content="Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><h1>Browse all tags</h1><ul class="all-tags"><li class="tag"><a href="/tags/article">article</a></li><li class="tag"><a href="/tags/codesnippet">code-snippet</a></li><li class="tag"><a href="/tags/colab">colab</a></li><li class="tag"><a href="/tags/helloworld">hello-world</a></li><li class="tag"><a href="/tags/kaggle">kaggle</a></li><li class="tag"><a href="/tags/publication">publication</a></li><li class="tag"><a href="/tags/swiftui">swiftUI</a></li><li class="tag"><a href="/tags/tensorflow">tensorflow</a></li><li class="tag"><a href="/tags/turicreate">turicreate</a></li><li class="tag"><a href="/tags/tutorial">tutorial</a></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
diff --git a/tags/kaggle/index.html b/tags/kaggle/index.html
new file mode 100644
index 0000000..02a7baa
--- /dev/null
+++ b/tags/kaggle/index.html
@@ -0,0 +1 @@
+<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/tags/kaggle"/><meta name="twitter:url" content="https://navanchauhan.github.io/tags/kaggle"/><meta name="og:url" content="https://navanchauhan.github.io/tags/kaggle"/><title>Navan Chauhan</title><meta name="twitter:title" content="Navan Chauhan"/><meta name="og:title" content="Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><h1>Tagged with <span class="tag">kaggle</span></h1><a class="browse-all" href="/tags">Browse all tags</a><ul class="item-list"><li><article><h1><a href="/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab">Setting up Kaggle to use with Google Colab</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li><li><a href="/tags/kaggle">kaggle</a></li></ul><span>🕑 1 minute read.</span><p>Tutorial on setting up kaggle, to use with Google Colab</p></article></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
diff --git a/tags/turicreate/index.html b/tags/turicreate/index.html
index b10b7f8..db64873 100644
--- a/tags/turicreate/index.html
+++ b/tags/turicreate/index.html
@@ -1 +1 @@
-<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/tags/turicreate"/><meta name="twitter:url" content="https://navanchauhan.github.io/tags/turicreate"/><meta name="og:url" content="https://navanchauhan.github.io/tags/turicreate"/><title>Navan Chauhan</title><meta name="twitter:title" content="Navan Chauhan"/><meta name="og:title" content="Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><h1>Tagged with <span class="tag">turicreate</span></h1><a class="browse-all" href="/tags">Browse all tags</a><ul class="item-list"><li><article><h1><a href="/posts/2019-12-22-Fake-News-Detector">Building a Fake News Detector with Turicreate</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/swiftui">swiftUI</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>In this tutorial we will build a fake news detecting app from scratch, using Turicreate for the machine learning model and SwiftUI for building the app</p></article></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
+<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/tags/turicreate"/><meta name="twitter:url" content="https://navanchauhan.github.io/tags/turicreate"/><meta name="og:url" content="https://navanchauhan.github.io/tags/turicreate"/><title>Navan Chauhan</title><meta name="twitter:title" content="Navan Chauhan"/><meta name="og:title" content="Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><h1>Tagged with <span class="tag">turicreate</span></h1><a class="browse-all" href="/tags">Browse all tags</a><ul class="item-list"><li><article><h1><a href="/posts/2020-01-16-Image-Classifier-Using-Turicreate">Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle</p></article></li><li><article><h1><a href="/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab">Setting up Kaggle to use with Google Colab</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li><li><a href="/tags/kaggle">kaggle</a></li></ul><span>🕑 1 minute read.</span><p>Tutorial on setting up kaggle, to use with Google Colab</p></article></li><li><article><h1><a href="/posts/2019-12-22-Fake-News-Detector">Building a Fake News Detector with Turicreate</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/swiftui">swiftUI</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>In this tutorial we will build a fake news detecting app from scratch, using Turicreate for the machine learning model and SwiftUI for building the app</p></article></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
diff --git a/tags/tutorial/index.html b/tags/tutorial/index.html
index 0e8002d..c2219e5 100644
--- a/tags/tutorial/index.html
+++ b/tags/tutorial/index.html
@@ -1 +1 @@
-<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/tags/tutorial"/><meta name="twitter:url" content="https://navanchauhan.github.io/tags/tutorial"/><meta name="og:url" content="https://navanchauhan.github.io/tags/tutorial"/><title>Navan Chauhan</title><meta name="twitter:title" content="Navan Chauhan"/><meta name="og:title" content="Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link rel="alternate" href="/feed.rss" type="application/rss+xml" title="Subscribe to Navan Chauhan"/><meta name="twitter:image" content="https://navanchauhan.github.io/images/logo.png"/><meta name="og:image" content="https://navanchauhan.github.io/images/logo.png"/></head><head><script src="https://www.googletagmanager.com/gtag/js?id=UA-108635191-1v"></script><script>window.dataLayer = window.dataLayer || [];function gtag(){dataLayer.push(arguments);}gtag('js', new Date());gtag('config', 'UA-108635191-1');</script></head><body><header><div class="wrapper"><a class="site-name" href="/">Navan Chauhan</a><nav><ul><li><a href="/about">About Me</a></li><li><a href="/posts">Posts</a></li><li><a href="/publications">Publications</a></li><li><a href="https://navanchauhan.github.io/assets/résumé.pdf">Résumé</a></li><li><a href="https://navanchauhan.github.io/repo">Repo</a></li></ul></nav></div></header><div class="wrapper"><h1>Tagged with <span class="tag">tutorial</span></h1><a class="browse-all" href="/tags">Browse all tags</a><ul class="item-list"><li><article><h1><a href="/posts/2020-01-14-Converting-between-PIL-NumPy">Converting between image and NumPy array</a></h1><ul class="tag-list"><li><a href="/tags/codesnippet">code-snippet</a></li><li><a href="/tags/tutorial">tutorial</a></li></ul><span>🕑 0 minute read.</span><p>Short code snippet for converting between PIL image and NumPy arrays.</p></article></li><li><article><h1><a href="/posts/2019-12-22-Fake-News-Detector">Building a Fake News Detector with Turicreate</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/swiftui">swiftUI</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>In this tutorial we will build a fake news detecting app from scratch, using Turicreate for the machine learning model and SwiftUI for building the app</p></article></li><li><article><h1><a href="/posts/2019-12-16-TensorFlow-Polynomial-Regression">Polynomial Regression Using TensorFlow</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 16 minute read.</span><p>Polynomial regression using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-10-TensorFlow-Model-Prediction">Making Predictions using Image Classifier (TensorFlow)</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/codesnippet">code-snippet</a></li></ul><span>🕑 1 minute read.</span><p>Making predictions for image classification models built using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-08-Image-Classifier-Tensorflow">Creating a Custom Image Classifier using Tensorflow 2.x and Keras for Detecting Malaria</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 4 minute read.</span><p>Tutorial on creating an image classifier model using TensorFlow which detects malaria</p></article></li><li><article><h1><a href="/posts/2019-12-08-Splitting-Zips">Splitting ZIPs into Multiple Parts</a></h1><ul class="tag-list"><li><a href="/tags/codesnippet">code-snippet</a></li><li><a href="/tags/tutorial">tutorial</a></li></ul><span>🕑 0 minute read.</span><p>Short code snippet for splitting zips.</p></article></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file
+<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8"/><meta name="og:site_name" content="Navan Chauhan"/><link rel="canonical" href="https://navanchauhan.github.io/tags/tutorial"/><meta name="twitter:url" content="https://navanchauhan.github.io/tags/tutorial"/><meta name="og:url" content="https://navanchauhan.github.io/tags/tutorial"/><title>Navan Chauhan</title><meta name="twitter:title" content="Navan Chauhan"/><meta name="og:title" content="Navan Chauhan"/><meta name="description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:description" content="Welcome to my personal fragment of the internet."/><meta name="og:description" content="Welcome to my personal fragment of the internet."/><meta name="twitter:card" content="summary"/><link rel="stylesheet" href="/styles.css" type="text/css"/><meta name="viewport" content="width=device-width, initial-scale=1.0"/><link rel="shortcut icon" href="/images/favicon.png" type="image/png"/><link 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href="/tags">Browse all tags</a><ul class="item-list"><li><article><h1><a href="/posts/2020-01-16-Image-Classifier-Using-Turicreate">Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>Tutorial on creating a custom Image Classifier using Turicreate and a dataset from Kaggle</p></article></li><li><article><h1><a href="/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab">Setting up Kaggle to use with Google Colab</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/turicreate">turicreate</a></li><li><a href="/tags/kaggle">kaggle</a></li></ul><span>🕑 1 minute read.</span><p>Tutorial on setting up kaggle, to use with Google Colab</p></article></li><li><article><h1><a href="/posts/2020-01-14-Converting-between-PIL-NumPy">Converting between image and NumPy array</a></h1><ul class="tag-list"><li><a href="/tags/codesnippet">code-snippet</a></li><li><a href="/tags/tutorial">tutorial</a></li></ul><span>🕑 0 minute read.</span><p>Short code snippet for converting between PIL image and NumPy arrays.</p></article></li><li><article><h1><a href="/posts/2019-12-22-Fake-News-Detector">Building a Fake News Detector with Turicreate</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/colab">colab</a></li><li><a href="/tags/swiftui">swiftUI</a></li><li><a href="/tags/turicreate">turicreate</a></li></ul><span>🕑 6 minute read.</span><p>In this tutorial we will build a fake news detecting app from scratch, using Turicreate for the machine learning model and SwiftUI for building the app</p></article></li><li><article><h1><a href="/posts/2019-12-16-TensorFlow-Polynomial-Regression">Polynomial Regression Using TensorFlow</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 16 minute read.</span><p>Polynomial regression using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-10-TensorFlow-Model-Prediction">Making Predictions using Image Classifier (TensorFlow)</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/codesnippet">code-snippet</a></li></ul><span>🕑 1 minute read.</span><p>Making predictions for image classification models built using TensorFlow</p></article></li><li><article><h1><a href="/posts/2019-12-08-Image-Classifier-Tensorflow">Creating a Custom Image Classifier using Tensorflow 2.x and Keras for Detecting Malaria</a></h1><ul class="tag-list"><li><a href="/tags/tutorial">tutorial</a></li><li><a href="/tags/tensorflow">tensorflow</a></li><li><a href="/tags/colab">colab</a></li></ul><span>🕑 4 minute read.</span><p>Tutorial on creating an image classifier model using TensorFlow which detects malaria</p></article></li><li><article><h1><a href="/posts/2019-12-08-Splitting-Zips">Splitting ZIPs into Multiple Parts</a></h1><ul class="tag-list"><li><a href="/tags/codesnippet">code-snippet</a></li><li><a href="/tags/tutorial">tutorial</a></li></ul><span>🕑 0 minute read.</span><p>Short code snippet for splitting zips.</p></article></li></ul></div><footer><p>Made with ❤️ using <a href="https://github.com/johnsundell/publish">Publish</a></p><p><a href="/feed.rss">RSS feed</a></p></footer></body></html> \ No newline at end of file