From 3ec7d22d1ca0c5a5bbd54a735f917aebab633928 Mon Sep 17 00:00:00 2001 From: Navan Chauhan Date: Mon, 1 Jun 2020 12:33:18 +0530 Subject: Publish deploy 2020-06-01 12:33 --- feed.rss | 2 +- index.html | 2 +- posts/2010-01-24-experiments/index.html | 2 +- posts/2019-05-05-Custom-Snowboard-Anemone-Theme/index.html | 4 ++-- posts/2019-12-04-Google-Teachable-Machines/index.html | 2 +- posts/2019-12-08-Image-Classifier-Tensorflow/index.html | 4 ++-- posts/2019-12-08-Splitting-Zips/index.html | 4 ++-- posts/2019-12-10-TensorFlow-Model-Prediction/index.html | 4 ++-- posts/2019-12-16-TensorFlow-Polynomial-Regression/index.html | 4 ++-- posts/2019-12-22-Fake-News-Detector/index.html | 4 ++-- posts/2020-01-14-Converting-between-PIL-NumPy/index.html | 4 ++-- posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colab/index.html | 4 ++-- posts/2020-01-16-Image-Classifier-Using-Turicreate/index.html | 4 ++-- .../2020-01-19-Connect-To-Bluetooth-Devices-Linux-Terminal/index.html | 2 +- posts/2020-03-03-Playing-With-Android-TV/index.html | 2 +- posts/2020-03-08-Making-Vaporwave-Track/index.html | 2 +- posts/2020-05-31-compiling-open-babel-on-ios/index.html | 2 +- .../index.html | 2 +- posts/hello-world/index.html | 2 +- posts/index.html | 2 +- sitemap.xml | 2 +- tags/android/index.html | 2 +- tags/androidtv/index.html | 2 +- tags/anemone/index.html | 2 +- tags/article/index.html | 1 - tags/cheminformatics/index.html | 2 +- tags/codesnippet/index.html | 2 +- tags/colab/index.html | 2 +- tags/designing/index.html | 2 +- tags/experiment/index.html | 2 +- tags/helloworld/index.html | 2 +- tags/index.html | 2 +- tags/ios/index.html | 2 +- tags/jailbreak/index.html | 2 +- tags/kaggle/index.html | 2 +- tags/linux/index.html | 2 +- tags/macos/index.html | 2 +- tags/moleculardocking/index.html | 2 +- tags/music/index.html | 2 +- tags/openbabel/index.html | 2 +- tags/pymol/index.html | 1 - tags/raspberrypi/index.html | 2 +- tags/snowboard/index.html | 2 +- tags/swiftui/index.html | 2 +- tags/tensorflow/index.html | 2 +- tags/turicreate/index.html | 2 +- tags/tutorial/index.html | 2 +- tags/vaporwave/index.html | 2 +- 48 files changed, 55 insertions(+), 57 deletions(-) delete mode 100644 tags/article/index.html delete mode 100644 tags/pymol/index.html diff --git a/feed.rss b/feed.rss index 3f63420..306d50a 100644 --- a/feed.rss +++ b/feed.rss @@ -1,4 +1,4 @@ -Navan ChauhanWelcome to my personal fragment of the internet. Majority of the posts should be complete.https://navanchauhan.github.io/enMon, 1 Jun 2020 12:27:03 +0530Mon, 1 Jun 2020 12:27:03 +0530250https://navanchauhan.github.io/posts/2020-06-01-Speeding-Up-Molecular-Docking-Workflow-AutoDock-Vina-and-PyMOLWorkflow for Lightning Fast Molecular Docking Part OneThis is my workflow for lightning fast molecular docking.https://navanchauhan.github.io/posts/2020-06-01-Speeding-Up-Molecular-Docking-Workflow-AutoDock-Vina-and-PyMOLMon, 1 Jun 2020 13:10:00 +0530Workflow for Lightning Fast Molecular Docking Part One

My Setup

  • macOS Catalina ( RIP 32bit app)
  • PyMOL
  • AutoDock Vina
  • Open Babel

One Command Docking

obabel -:"$(pbpaste)" --gen3d -opdbqt -Otest.pdbqt && vina --receptor lu.pdbqt --center_x -9.7 --center_y 11.4 --center_z 68.9 --size_x 19.3 --size_y 29.9 --size_z 21.3  --ligand test.pdbqt
+Navan ChauhanWelcome to my personal fragment of the internet. Majority of the posts should be complete.https://navanchauhan.github.io/enMon, 1 Jun 2020 12:33:11 +0530Mon, 1 Jun 2020 12:33:11 +0530250https://navanchauhan.github.io/posts/2020-06-01-Speeding-Up-Molecular-Docking-Workflow-AutoDock-Vina-and-PyMOLWorkflow for Lightning Fast Molecular Docking Part OneThis is my workflow for lightning fast molecular docking.https://navanchauhan.github.io/posts/2020-06-01-Speeding-Up-Molecular-Docking-Workflow-AutoDock-Vina-and-PyMOLMon, 1 Jun 2020 13:10:00 +0530Workflow for Lightning Fast Molecular Docking Part One
My Setup
  • macOS Catalina ( RIP 32bit app)
  • PyMOL
  • AutoDock Vina
  • Open Babel
One Command Docking
obabel -:"$(pbpaste)" --gen3d -opdbqt -Otest.pdbqt && vina --receptor lu.pdbqt --center_x -9.7 --center_y 11.4 --center_z 68.9 --size_x 19.3 --size_y 29.9 --size_z 21.3  --ligand test.pdbqt
 
To run this command you simple copy the SMILES structure of the ligand you want an it automatically takes it from your clipboard, generates the 3D structure in the AutoDock PDBQT format using Open Babel and then docks it with your receptor using AutoDock Vina, all with just one command.
Let me break down the commands
obabel -:"$(pbpaste)" --gen3d -opdbqt -Otest.pdbqt
 
pbpaste and pbcopy are macOS commands for pasting and copying from and to the clipboard. Linux users may install the xclip and xsel packages from their respective package managers and then insert these aliases into their bash_profile, zshrc e.t.c
alias pbcopy='xclip -selection clipboard'
 alias pbpaste='xclip -selection clipboard -o'
diff --git a/index.html b/index.html
index 0571d10..4141e48 100644
--- a/index.html
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@@ -1 +1 @@
-Hi! | Navan Chauhan
Navan Chauhan
Hi!
Welcome to my personal fragment of the internet. Majority of the posts should be complete.
Latest content

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+Hi! | Navan Chauhan
Navan Chauhan
Hi!
Welcome to my personal fragment of the internet. Majority of the posts should be complete.
Latest content

\ No newline at end of file
diff --git a/posts/2010-01-24-experiments/index.html b/posts/2010-01-24-experiments/index.html
index bfe9346..39c2a0f 100644
--- a/posts/2010-01-24-experiments/index.html
+++ b/posts/2010-01-24-experiments/index.html
@@ -1 +1 @@
-Experiments | Navan Chauhan
Navan Chauhan
1 minute readCreated on January 24, 2010Last modified on February 4, 2020
Experiments
https://s3-us-west-2.amazonaws.com/s.cdpn.io/148866/img-original.jpg
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+Experiments | Navan Chauhan
Navan Chauhan
1 minute readCreated on January 24, 2010Last modified on June 1, 2020
Experiments
https://s3-us-west-2.amazonaws.com/s.cdpn.io/148866/img-original.jpg
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diff --git a/posts/2019-05-05-Custom-Snowboard-Anemone-Theme/index.html b/posts/2019-05-05-Custom-Snowboard-Anemone-Theme/index.html
index 943eb35..1eda74a 100644
--- a/posts/2019-05-05-Custom-Snowboard-Anemone-Theme/index.html
+++ b/posts/2019-05-05-Custom-Snowboard-Anemone-Theme/index.html
@@ -1,4 +1,4 @@
-Creating your own custom theme for Snowboard or Anemone | Navan Chauhan
Navan Chauhan
5 minute readCreated on May 5, 2019Last modified on March 9, 2020
Creating your own custom theme for Snowboard or Anemone
Contents
  • Getting Started
  • Theme Configuration
  • Creating Icons
  • Exporting Icons
  • Icon Masks
  • Packaging
  • Building the DEB
Getting Started
Note: Without the proper folder structure, your theme may not show up!
  • Create a new folder called themeName.theme (Replace themeName with your desired theme name)
  • Within themeName.theme folder, create another folder called IconBundles (You cannot change this name)
Theme Configuration
  • Now, inside the themeName.theme folder, create a file called Info.plist and paste the following
<?xml version="1.0" encoding="UTF-8"?>
+Creating your own custom theme for Snowboard or Anemone | Navan Chauhan
Navan Chauhan
5 minute readCreated on May 5, 2019Last modified on June 1, 2020
Creating your own custom theme for Snowboard or Anemone
Contents
  • Getting Started
  • Theme Configuration
  • Creating Icons
  • Exporting Icons
  • Icon Masks
  • Packaging
  • Building the DEB
Getting Started
Note: Without the proper folder structure, your theme may not show up!
  • Create a new folder called themeName.theme (Replace themeName with your desired theme name)
  • Within themeName.theme folder, create another folder called IconBundles (You cannot change this name)
Theme Configuration
  • Now, inside the themeName.theme folder, create a file called Info.plist and paste the following
<?xml version="1.0" encoding="UTF-8"?>
 <!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
   <plist version="1.0">
   <dict>
@@ -114,4 +114,4 @@ DEBIAN  Library
 **Now you will have the `themeNameForCydia.deb` in the same directory**
 
 You can share this with your friends :+1:
-
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diff --git a/posts/2019-12-04-Google-Teachable-Machines/index.html b/posts/2019-12-04-Google-Teachable-Machines/index.html
index 3c5befa..1a090b9 100644
--- a/posts/2019-12-04-Google-Teachable-Machines/index.html
+++ b/posts/2019-12-04-Google-Teachable-Machines/index.html
@@ -1 +1 @@
-Image Classifier With Teachable Machines | Navan Chauhan
Navan Chauhan
2 minute readCreated on December 4, 2019Last modified on March 9, 2020
Image Classifier With Teachable Machines
Made for Google Code-In
Task Description
Using Glitch and the Teachable Machines, build a Book Detector with Tensorflow.js. When a book is recognized, the code would randomly suggest a book/tell a famous quote from a book. Here is an example Project to get you started: https://glitch.com/~voltaic-acorn
Details
  1. Collecting Data
Teachable Machine allows you to create your dataset just by using your webcam! I created a database consisting of three classes ( Three Books ) and approximately grabbed 100 pictures for each book/class
  1. Training
Training on teachable machines is as simple as clicking the train button. I did not even have to modify any configurations.
  1. Finding Labels
Because I originally entered the entire name of the book and it's author's name as the label, the class name got truncated (Note to self, use shorter class names :p ). I then modified the code to print the modified label names in an alert box.
  1. Adding a suggestions function
I first added a text field on the main page and then modified the JavaScript file to suggest a similar book whenever the model predicted with an accuracy >= 98%
  1. Running!
Here it is running!
Remix this project:-
https://luminous-opinion.glitch.me
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+Image Classifier With Teachable Machines | Navan Chauhan
Navan Chauhan
2 minute readCreated on December 4, 2019Last modified on June 1, 2020
Image Classifier With Teachable Machines
Made for Google Code-In
Task Description
Using Glitch and the Teachable Machines, build a Book Detector with Tensorflow.js. When a book is recognized, the code would randomly suggest a book/tell a famous quote from a book. Here is an example Project to get you started: https://glitch.com/~voltaic-acorn
Details
  1. Collecting Data
Teachable Machine allows you to create your dataset just by using your webcam! I created a database consisting of three classes ( Three Books ) and approximately grabbed 100 pictures for each book/class
  1. Training
Training on teachable machines is as simple as clicking the train button. I did not even have to modify any configurations.
  1. Finding Labels
Because I originally entered the entire name of the book and it's author's name as the label, the class name got truncated (Note to self, use shorter class names :p ). I then modified the code to print the modified label names in an alert box.
  1. Adding a suggestions function
I first added a text field on the main page and then modified the JavaScript file to suggest a similar book whenever the model predicted with an accuracy >= 98%
  1. Running!
Here it is running!
Remix this project:-
https://luminous-opinion.glitch.me
Tagged with: 

\ No newline at end of file
diff --git a/posts/2019-12-08-Image-Classifier-Tensorflow/index.html b/posts/2019-12-08-Image-Classifier-Tensorflow/index.html
index 0822e30..5cf20ba 100644
--- a/posts/2019-12-08-Image-Classifier-Tensorflow/index.html
+++ b/posts/2019-12-08-Image-Classifier-Tensorflow/index.html
@@ -1,4 +1,4 @@
-Creating a Custom Image Classifier using Tensorflow 2.x and Keras for Detecting Malaria | Navan Chauhan
Navan Chauhan
4 minute readCreated on December 8, 2019Last modified on May 24, 2020
Creating a Custom Image Classifier using Tensorflow 2.x and Keras for Detecting Malaria
Done during Google Code-In. Org: Tensorflow.
Imports
%tensorflow_version 2.x #This is for telling Colab that you want to use TF 2.0, ignore if running on local machine
+Creating a Custom Image Classifier using Tensorflow 2.x and Keras for Detecting Malaria | Navan Chauhan
Navan Chauhan
4 minute readCreated on December 8, 2019Last modified on June 1, 2020
Creating a Custom Image Classifier using Tensorflow 2.x and Keras for Detecting Malaria
Done during Google Code-In. Org: Tensorflow.
Imports
%tensorflow_version 2.x #This is for telling Colab that you want to use TF 2.0, ignore if running on local machine
 
 from PIL import Image # We use the PIL Library to resize images
 import numpy as np
@@ -98,4 +98,4 @@ np.random.shuffle(s)
 Loss: 3.732407123270176 
 Validation Accuracy: 100.0 
 Validation Loss: 0.0
-
We have achieved 98% Accuracy!
Link to Colab Notebook
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We have achieved 98% Accuracy!
Link to Colab Notebook
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diff --git a/posts/2019-12-08-Splitting-Zips/index.html b/posts/2019-12-08-Splitting-Zips/index.html
index 17da0d6..735c37c 100644
--- a/posts/2019-12-08-Splitting-Zips/index.html
+++ b/posts/2019-12-08-Splitting-Zips/index.html
@@ -1,4 +1,4 @@
-Splitting ZIPs into Multiple Parts | Navan Chauhan
Navan Chauhan
1 minute readCreated on December 8, 2019Last modified on January 18, 2020
Splitting ZIPs into Multiple Parts
Tested on macOS
Creating the archive:
zip -r -s 5 oodlesofnoodles.zip website/
+Splitting ZIPs into Multiple Parts | Navan Chauhan
Navan Chauhan
1 minute readCreated on December 8, 2019Last modified on June 1, 2020
Splitting ZIPs into Multiple Parts
Tested on macOS
Creating the archive:
zip -r -s 5 oodlesofnoodles.zip website/
 
5 stands for each split files' size (in mb, kb and gb can also be specified)
For encrypting the zip:
zip -er -s 5 oodlesofnoodles.zip website
 
Extracting Files
First we need to collect all parts, then
zip -F oodlesofnoodles.zip --out merged.zip
-
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diff --git a/posts/2019-12-10-TensorFlow-Model-Prediction/index.html b/posts/2019-12-10-TensorFlow-Model-Prediction/index.html
index da7cae5..5f73c10 100644
--- a/posts/2019-12-10-TensorFlow-Model-Prediction/index.html
+++ b/posts/2019-12-10-TensorFlow-Model-Prediction/index.html
@@ -1,4 +1,4 @@
-Making Predictions using Image Classifier (TensorFlow) | Navan Chauhan
Navan Chauhan
1 minute readCreated on December 10, 2019Last modified on January 18, 2020
Making Predictions using Image Classifier (TensorFlow)
This was tested on TF 2.x and works as of 2019-12-10
If you want to understand how to make your own custom image classifier, please refer to my previous post.
If you followed my last post, then you created a model which took an image of dimensions 50x50 as an input.
First we import the following if we have not imported these before
import cv2
+Making Predictions using Image Classifier (TensorFlow) | Navan Chauhan
Navan Chauhan
1 minute readCreated on December 10, 2019Last modified on June 1, 2020
Making Predictions using Image Classifier (TensorFlow)
This was tested on TF 2.x and works as of 2019-12-10
If you want to understand how to make your own custom image classifier, please refer to my previous post.
If you followed my last post, then you created a model which took an image of dimensions 50x50 as an input.
First we import the following if we have not imported these before
import cv2
 import os
 
Then we read the file using OpenCV.
image=cv2.imread(imagePath)
 
The cv2. imread() function returns a NumPy array representing the image. Therefore, we need to convert it before we can use it.
image_from_array = Image.fromarray(image, 'RGB')
@@ -6,4 +6,4 @@
 
After this we create a batch consisting of only one image
p = np.expand_dims(size_image, 0)
 
We then convert this uint8 datatype to a float32 datatype
img = tf.cast(p, tf.float32)
 
Finally we make the prediction
print(['Infected','Uninfected'][np.argmax(model.predict(img))])
-
Infected
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Infected
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diff --git a/posts/2019-12-16-TensorFlow-Polynomial-Regression/index.html b/posts/2019-12-16-TensorFlow-Polynomial-Regression/index.html
index 5365d89..5ae4c38 100644
--- a/posts/2019-12-16-TensorFlow-Polynomial-Regression/index.html
+++ b/posts/2019-12-16-TensorFlow-Polynomial-Regression/index.html
@@ -1,4 +1,4 @@
-Polynomial Regression Using TensorFlow | Navan Chauhan
Navan Chauhan
17 minute readCreated on December 16, 2019Last modified on January 18, 2020
Polynomial Regression Using TensorFlow
In this tutorial you will learn about polynomial regression and how you can implement it in Tensorflow.
In this, we will be performing polynomial regression using 5 types of equations -
  • Linear
  • Quadratic
  • Cubic
  • Quartic
  • Quintic
Regression
What is Regression?
Regression is a statistical measurement that is used to try to determine the relationship between a dependent variable (often denoted by Y), and series of varying variables (called independent variables, often denoted by X ).
What is Polynomial Regression
This is a form of Regression Analysis where the relationship between Y and X is denoted as the nth degree/power of X. Polynomial regression even fits a non-linear relationship (e.g when the points don't form a straight line).
Imports
import tensorflow.compat.v1 as tf
+Polynomial Regression Using TensorFlow | Navan Chauhan
Navan Chauhan
17 minute readCreated on December 16, 2019Last modified on June 1, 2020
Polynomial Regression Using TensorFlow
In this tutorial you will learn about polynomial regression and how you can implement it in Tensorflow.
In this, we will be performing polynomial regression using 5 types of equations -
  • Linear
  • Quadratic
  • Cubic
  • Quartic
  • Quintic
Regression
What is Regression?
Regression is a statistical measurement that is used to try to determine the relationship between a dependent variable (often denoted by Y), and series of varying variables (called independent variables, often denoted by X ).
What is Polynomial Regression
This is a form of Regression Analysis where the relationship between Y and X is denoted as the nth degree/power of X. Polynomial regression even fits a non-linear relationship (e.g when the points don't form a straight line).
Imports
import tensorflow.compat.v1 as tf
 tf.disable_v2_behavior()
 import matplotlib.pyplot as plt
 import numpy as np
@@ -304,4 +304,4 @@
 plt.title('Quintic Regression Result')
 plt.legend()
 plt.show()
-
Results and Conclusion
You just learnt Polynomial Regression using TensorFlow!
Notes
Overfitting
> Overfitting refers to a model that models the training data too well.Overfitting happens when a model learns the detail and noise in the training data to the extent that it negatively impacts the performance of the model on new data. This means that the noise or random fluctuations in the training data is picked up and learned as concepts by the model. The problem is that these concepts do not apply to new data and negatively impact the models ability to generalize.
Source: Machine Learning Mastery
Basically if you train your machine learning model on a small dataset for a really large number of epochs, the model will learn all the deformities/noise in the data and will actually think that it is a normal part. Therefore when it will see some new data, it will discard that new data as noise and will impact the accuracy of the model in a negative manner
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+
Results and Conclusion
You just learnt Polynomial Regression using TensorFlow!
Notes
Overfitting
> Overfitting refers to a model that models the training data too well.Overfitting happens when a model learns the detail and noise in the training data to the extent that it negatively impacts the performance of the model on new data. This means that the noise or random fluctuations in the training data is picked up and learned as concepts by the model. The problem is that these concepts do not apply to new data and negatively impact the models ability to generalize.
Source: Machine Learning Mastery
Basically if you train your machine learning model on a small dataset for a really large number of epochs, the model will learn all the deformities/noise in the data and will actually think that it is a normal part. Therefore when it will see some new data, it will discard that new data as noise and will impact the accuracy of the model in a negative manner
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diff --git a/posts/2019-12-22-Fake-News-Detector/index.html b/posts/2019-12-22-Fake-News-Detector/index.html
index 96ebd30..818fbed 100644
--- a/posts/2019-12-22-Fake-News-Detector/index.html
+++ b/posts/2019-12-22-Fake-News-Detector/index.html
@@ -1,4 +1,4 @@
-Building a Fake News Detector with Turicreate | Navan Chauhan
Navan Chauhan
7 minute readCreated on December 22, 2019Last modified on January 18, 2020
Building a Fake News Detector with Turicreate
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
Note: These commands are written as if you are running a jupyter notebook.
Building the Machine Learning Model
Data Gathering
To build a classifier, you need a lot of data. George McIntire (GH: @joolsa) has created a wonderful dataset containing the headline, body and wheter it is fake or real. Whenever you are looking for a dataset, always try searching on Kaggle and GitHub before you start building your own
Dependencies
I used a Google Colab instance for training my model. If you also plan on using Google Colab then I reccomend choosing a GPU Instance (It is Free) This allows you to train the model on the GPU. Turicreat is built on top of Apache's MXNet Framework, for us to use GPU we need to install a CUDA compatible MXNet package.
!pip install turicreate
+Building a Fake News Detector with Turicreate | Navan Chauhan
Navan Chauhan
7 minute readCreated on December 22, 2019Last modified on June 1, 2020
Building a Fake News Detector with Turicreate
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
Note: These commands are written as if you are running a jupyter notebook.
Building the Machine Learning Model
Data Gathering
To build a classifier, you need a lot of data. George McIntire (GH: @joolsa) has created a wonderful dataset containing the headline, body and wheter it is fake or real. Whenever you are looking for a dataset, always try searching on Kaggle and GitHub before you start building your own
Dependencies
I used a Google Colab instance for training my model. If you also plan on using Google Colab then I reccomend choosing a GPU Instance (It is Free) This allows you to train the model on the GPU. Turicreat is built on top of Apache's MXNet Framework, for us to use GPU we need to install a CUDA compatible MXNet package.
!pip install turicreate
 !pip uninstall -y mxnet
 !pip install mxnet-cu100==1.4.0.post0
 
If you do not wish to train on GPU or are running it on your computer, you can ignore the last two lines
Downloading the Dataset
!wget -q "https://github.com/joolsa/fake_real_news_dataset/raw/master/fake_or_real_news.csv.zip"
@@ -138,4 +138,4 @@
         ContentView()
     }
 }
-
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diff --git a/posts/2020-01-14-Converting-between-PIL-NumPy/index.html b/posts/2020-01-14-Converting-between-PIL-NumPy/index.html
index 13cd71d..8d0fe0a 100644
--- a/posts/2020-01-14-Converting-between-PIL-NumPy/index.html
+++ b/posts/2020-01-14-Converting-between-PIL-NumPy/index.html
@@ -1,4 +1,4 @@
-Converting between image and NumPy array | Navan Chauhan
Navan Chauhan
1 minute readCreated on January 14, 2020Last modified on March 9, 2020
Converting between image and NumPy array
import numpy
+Converting between image and NumPy array | Navan Chauhan
Navan Chauhan
1 minute readCreated on January 14, 2020Last modified on June 1, 2020
Converting between image and NumPy array
import numpy
 import PIL
 
 # Convert PIL Image to NumPy array
@@ -12,4 +12,4 @@
 except IOError:
     PIL.ImageFile.MAXBLOCK = img.size[0] * img.size[1]
     img.save(destination, "JPEG", quality=80, optimize=True, progressive=True)
-
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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
index 229d6dd..9e5343d 100644
--- 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
@@ -1,5 +1,5 @@
-Setting up Kaggle to use with Google Colab | Navan Chauhan
Navan Chauhan
1 minute readCreated on January 15, 2020Last modified on January 19, 2020
Setting up Kaggle to use with Google Colab
In order to be able to access Kaggle Datasets, you will need to have an account on Kaggle (which is Free)
Grabbing Our Tokens
Go to Kaggle
Click on your User Profile and Click on My Account
Scroll Down untill you see Create New API Token
This will download your token as a JSON file
Copy the File to the root folder of your Google Drive
Setting up Colab
Mounting Google Drive
import os
+Setting up Kaggle to use with Google Colab | Navan Chauhan
Navan Chauhan
1 minute readCreated on January 15, 2020Last modified on June 1, 2020
Setting up Kaggle to use with Google Colab
In order to be able to access Kaggle Datasets, you will need to have an account on Kaggle (which is Free)
Grabbing Our Tokens
Go to Kaggle
Click on your User Profile and Click on My Account
Scroll Down untill you see Create New API Token
This will download your token as a JSON file
Copy the File to the root folder of your Google Drive
Setting up Colab
Mounting Google Drive
import os
 from google.colab import drive
 drive.mount('/content/drive')
 
After this click on the URL in the output section, login and then paste the Auth Code
Configuring Kaggle
os.environ['KAGGLE_CONFIG_DIR'] = "/content/drive/My Drive/"
-
Voila! You can now download kaggel datasets
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+
Voila! You can now download kaggel datasets
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diff --git a/posts/2020-01-16-Image-Classifier-Using-Turicreate/index.html b/posts/2020-01-16-Image-Classifier-Using-Turicreate/index.html
index f21e657..a09d839 100644
--- a/posts/2020-01-16-Image-Classifier-Using-Turicreate/index.html
+++ b/posts/2020-01-16-Image-Classifier-Using-Turicreate/index.html
@@ -1,4 +1,4 @@
-Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire | Navan Chauhan
Navan Chauhan
6 minute readCreated on January 16, 2020Last modified on January 19, 2020
Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire
For setting up Kaggle with Google Colab, please refer to  my previous post
Dataset
Mounting Google Drive
import os
+Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire | Navan Chauhan
Navan Chauhan
6 minute readCreated on January 16, 2020Last modified on June 1, 2020
Creating a Custom Image Classifier using Turicreate to detect Smoke and Fire
For setting up Kaggle with Google Colab, please refer to  my previous post
Dataset
Mounting Google Drive
import os
 from google.colab import drive
 drive.mount('/content/drive')
 
Downloading Dataset from Kaggle
os.environ['KAGGLE_CONFIG_DIR'] = "/content/drive/My Drive/"
@@ -186,4 +186,4 @@
 Completed 384/395
 Completed 395/395
 0.9316455696202531
-
We just got an accuracy of 94% on Training Data and 97% on Validation Data!
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+
We just got an accuracy of 94% on Training Data and 97% on Validation Data!
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\ No newline at end of file
diff --git a/posts/2020-01-19-Connect-To-Bluetooth-Devices-Linux-Terminal/index.html b/posts/2020-01-19-Connect-To-Bluetooth-Devices-Linux-Terminal/index.html
index c45b34e..7fd3bd5 100644
--- a/posts/2020-01-19-Connect-To-Bluetooth-Devices-Linux-Terminal/index.html
+++ b/posts/2020-01-19-Connect-To-Bluetooth-Devices-Linux-Terminal/index.html
@@ -1 +1 @@
-How to setup Bluetooth on a Raspberry Pi | Navan Chauhan
Navan Chauhan
1 minute readCreated on January 19, 2020Last modified on January 20, 2020
How to setup Bluetooth on a Raspberry Pi
This was tested on a Raspberry Pi Zero W
Enter in the Bluetooth Mode
pi@raspberrypi:~ $ bluetoothctl
[bluetooth]# agent on
[bluetooth]# default-agent
[bluetooth]# scan on
To Pair
While being in bluetooth mode
[bluetooth]# pair XX:XX:XX:XX:XX:XX
To Exit out of bluetoothctl anytime, just type exit
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\ No newline at end of file
+How to setup Bluetooth on a Raspberry Pi | Navan Chauhan
Navan Chauhan
1 minute readCreated on January 19, 2020Last modified on June 1, 2020
How to setup Bluetooth on a Raspberry Pi
This was tested on a Raspberry Pi Zero W
Enter in the Bluetooth Mode
pi@raspberrypi:~ $ bluetoothctl
[bluetooth]# agent on
[bluetooth]# default-agent
[bluetooth]# scan on
To Pair
While being in bluetooth mode
[bluetooth]# pair XX:XX:XX:XX:XX:XX
To Exit out of bluetoothctl anytime, just type exit
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\ No newline at end of file
diff --git a/posts/2020-03-03-Playing-With-Android-TV/index.html b/posts/2020-03-03-Playing-With-Android-TV/index.html
index 9269d7e..0ba6dad 100644
--- a/posts/2020-03-03-Playing-With-Android-TV/index.html
+++ b/posts/2020-03-03-Playing-With-Android-TV/index.html
@@ -1 +1 @@
-Tinkering with an Android TV | Navan Chauhan
Navan Chauhan
1 minute readCreated on March 3, 2020Last modified on March 10, 2020
Tinkering with an Android TV
So I have an Android TV, this posts covers everything I have tried on it
Contents
  1. Getting TV's IP Address
  2. Enable Developer Settings
  3. Enable ADB
  4. Connect ADB
  5. Manipulating Packages
IP-Address
These steps should be similar for all Android-TVs
  • Go To Settings
  • Go to Network
  • Advanced Settings
  • Network Status
  • Note Down IP-Address
The other option is to go to your router's server page and get connected devices
Developer-Settings
  • Go To Settings
  • About
  • Continously click on the "Build" option until it says "You are a Developer"
Enable-ADB
  • Go to Settings
  • Go to Developer Options
  • Scroll untill you find ADB Debugging and enable that option
Connect-ADB
  • Open Terminal (Make sure you have ADB installed)
  • Enter the following command adb connect <IP_ADDRESS>
  • To test the connection run adb logcat
Manipulating Apps / Packages
Listing Packages
  • adb shell
  • pm list packages
Installing Packages
  • adb install -r package.apk
Uninstalling Packages
  • adb uninstall com.company.yourpackagename
Tagged with: 

\ No newline at end of file
+Tinkering with an Android TV | Navan Chauhan
Navan Chauhan
1 minute readCreated on March 3, 2020Last modified on June 1, 2020
Tinkering with an Android TV
So I have an Android TV, this posts covers everything I have tried on it
Contents
  1. Getting TV's IP Address
  2. Enable Developer Settings
  3. Enable ADB
  4. Connect ADB
  5. Manipulating Packages
IP-Address
These steps should be similar for all Android-TVs
  • Go To Settings
  • Go to Network
  • Advanced Settings
  • Network Status
  • Note Down IP-Address
The other option is to go to your router's server page and get connected devices
Developer-Settings
  • Go To Settings
  • About
  • Continously click on the "Build" option until it says "You are a Developer"
Enable-ADB
  • Go to Settings
  • Go to Developer Options
  • Scroll untill you find ADB Debugging and enable that option
Connect-ADB
  • Open Terminal (Make sure you have ADB installed)
  • Enter the following command adb connect <IP_ADDRESS>
  • To test the connection run adb logcat
Manipulating Apps / Packages
Listing Packages
  • adb shell
  • pm list packages
Installing Packages
  • adb install -r package.apk
Uninstalling Packages
  • adb uninstall com.company.yourpackagename
Tagged with: 

\ No newline at end of file
diff --git a/posts/2020-03-08-Making-Vaporwave-Track/index.html b/posts/2020-03-08-Making-Vaporwave-Track/index.html
index 8601e9b..8b40392 100644
--- a/posts/2020-03-08-Making-Vaporwave-Track/index.html
+++ b/posts/2020-03-08-Making-Vaporwave-Track/index.html
@@ -1 +1 @@
-Making My First Vaporwave Track (Remix) | Navan Chauhan
Navan Chauhan
2 minute readCreated on March 8, 2020
Making My First Vaporwave Track (Remix)
I finally completed my first quick and dirty vaporwave remix of "I Want It That Way" by the Backstreet Boys
V A P O R W A V E
Vaporwave is all about A E S T H E T I C S. Vaporwave is a type of music genre that emmerged as a parody of Chillwave, shared more as a meme rather than a proper musical genre. Of course this changed as the genre become mature
How to Vaporwave
The first track which is considered to be actual Vaporwave is Ramona Xavier's Macintosh Plus, this unspokenly set the the guidelines for making Vaporwave
  • Take a 1980s RnB song
  • Slow it down
  • Add Bass and Trebble
  • Add again
  • Add Reverb ( make sure its wet )
There you have your very own Vaporwave track.
( Now, there are some tracks being produced which are not remixes and are original )
My Remix
Where is the Programming?
The fact that there are steps on producing Vaporwave, this gave me the idea that Vaporwave can actually be made using programming, stay tuned for when I publish the program which I am working on ( Generating A E S T H E T I C artwork and remixes)
Tagged with: 

\ No newline at end of file
+Making My First Vaporwave Track (Remix) | Navan Chauhan
Navan Chauhan
2 minute readCreated on March 8, 2020Last modified on June 1, 2020
Making My First Vaporwave Track (Remix)
I finally completed my first quick and dirty vaporwave remix of "I Want It That Way" by the Backstreet Boys
V A P O R W A V E
Vaporwave is all about A E S T H E T I C S. Vaporwave is a type of music genre that emmerged as a parody of Chillwave, shared more as a meme rather than a proper musical genre. Of course this changed as the genre become mature
How to Vaporwave
The first track which is considered to be actual Vaporwave is Ramona Xavier's Macintosh Plus, this unspokenly set the the guidelines for making Vaporwave
  • Take a 1980s RnB song
  • Slow it down
  • Add Bass and Trebble
  • Add again
  • Add Reverb ( make sure its wet )
There you have your very own Vaporwave track.
( Now, there are some tracks being produced which are not remixes and are original )
My Remix
Where is the Programming?
The fact that there are steps on producing Vaporwave, this gave me the idea that Vaporwave can actually be made using programming, stay tuned for when I publish the program which I am working on ( Generating A E S T H E T I C artwork and remixes)
Tagged with: 

\ No newline at end of file
diff --git a/posts/2020-05-31-compiling-open-babel-on-ios/index.html b/posts/2020-05-31-compiling-open-babel-on-ios/index.html
index 0adbc68..2987563 100644
--- a/posts/2020-05-31-compiling-open-babel-on-ios/index.html
+++ b/posts/2020-05-31-compiling-open-babel-on-ios/index.html
@@ -40,4 +40,4 @@ make[1]: **
 make: *** [Makefile:129: all] Error 2
 
Strange but it is alright, there is nothing that hasn't been answered on the internet.
I did a little digging around and could not find a solution 😔
As a temporary fix, I disabled multithreading by going and commenting the lines in the source code.
Packaging as a deb
This was pretty straight forward, I tried installing it on my iPad and it was working pretty smoothly.
Moment of Truth
So I airdropped the .deb to my phone and tried installing it, the installation was succesful but when I tried obabel it just abborted.
Turns out because I had created an install target of a seprate folder while compiling, the binaries were refferencing a non-existing dylib rather than those in the /usr/lib folder. As a quick workaround I transferred the deb folder to my laptop and used otool and install_name tool: install_name_tool -change /var/root/obabel/ob-build/lib/libopenbabel.7.dylib /usr/lib/libopenbabel.7.dylib for all the executables and then signed them using jtool
I then installed it and everything went smoothly, I even ran obabel and it executed perfectly, showing the version number 3.1.0 ✌️ Ahh, smooth victory.
Nope. When I tried converting from SMILES to pdbqt, it gave an error saying plugin not found. This was weird.
So I just copied the entire build folder from my iPad to my phone and tried runnig it. Oops, Apple Sandbox Error, Oh no!
I spent 2 hours around this problem, only to see the documentation and relaise I hadn't setup the environment variable 🤦‍♂️
The Final Fix ( For Now )
export BABEL_DATADIR="/usr/share/openbabel/3.1.0"
 export BABEL_LIBDIR="/usr/lib/openbabel/3.1.0"
-
This was the tragedy of trying to compile something without knowing enough about compiling. It is 11:30 as of writing this. Something as trivial as this should not have taken me so long. Am I going to try to compile AutoDock Vina next? 🤔 Maybe.
Also, if you want to try Open Babel on you jailbroken iDevice, install the package from my repository ( You, need to run the above mentioned final fix :p ). This was tested on iOS 13.5, I cannot tell if it will work on others or not.
Hopefully, I add some more screenshots to this post.
Edit 1: Added Screenshots, had to replicate the errors.
Tagged with: 

\ No newline at end of file
+

This was the tragedy of trying to compile something without knowing enough about compiling. It is 11:30 as of writing this. Something as trivial as this should not have taken me so long. Am I going to try to compile AutoDock Vina next? 🤔 Maybe.

Also, if you want to try Open Babel on you jailbroken iDevice, install the package from my repository ( You, need to run the above mentioned final fix :p ). This was tested on iOS 13.5, I cannot tell if it will work on others or not.

Hopefully, I add some more screenshots to this post.

Edit 1: Added Screenshots, had to replicate the errors.

Tagged with:
\ No newline at end of file diff --git a/posts/2020-06-01-Speeding-Up-Molecular-Docking-Workflow-AutoDock-Vina-and-PyMOL/index.html b/posts/2020-06-01-Speeding-Up-Molecular-Docking-Workflow-AutoDock-Vina-and-PyMOL/index.html index aa9ff67..f7ac7fa 100644 --- a/posts/2020-06-01-Speeding-Up-Molecular-Docking-Workflow-AutoDock-Vina-and-PyMOL/index.html +++ b/posts/2020-06-01-Speeding-Up-Molecular-Docking-Workflow-AutoDock-Vina-and-PyMOL/index.html @@ -5,4 +5,4 @@ 
$(pbpaste)

This is used in bash to evaluate the results of a command. In this scenario we are using it to get the contents of the clipboard.

The rest of the command is a normal Open Babel command to generate a 3D structure in PDBQT format and then save it as test.pdbqt

&&

This tells the termianl to only run the next part if the previous command runs succesfuly without any errors.

vina --receptor lu.pdbqt --center_x -9.7 --center_y 11.4 --center_z 68.9 --size_x 19.3 --size_y 29.9 --size_z 21.3  --ligand test.pdbqt
-

This is just the docking command for AutoDock Vina. In the next part I will tell how to use PyMOL and a plugin to directly generate the coordinates in Vina format --center_x -9.7 --center_y 11.4 --center_z 68.9 --size_x 19.3 --size_y 29.9 --size_z 21.3 without needing to type them manually.

Tagged with:
\ No newline at end of file +

This is just the docking command for AutoDock Vina. In the next part I will tell how to use PyMOL and a plugin to directly generate the coordinates in Vina format --center_x -9.7 --center_y 11.4 --center_z 68.9 --size_x 19.3 --size_y 29.9 --size_z 21.3 without needing to type them manually.

Tagged with:
\ No newline at end of file diff --git a/posts/hello-world/index.html b/posts/hello-world/index.html index 06ae0df..ffcb541 100644 --- a/posts/hello-world/index.html +++ b/posts/hello-world/index.html @@ -1 +1 @@ -Hello World | Navan Chauhan
Navan Chauhan
1 minute readCreated on April 16, 2019Last modified on January 4, 2020

Hello World

Why a Hello World post?

Just re-did the entire website using Publish (Publish by John Sundell). So, a new hello world post :)

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\ No newline at end of file +Hello World | Navan Chauhan
Navan Chauhan
1 minute readCreated on April 16, 2019Last modified on June 1, 2020

Hello World

Why a Hello World post?

Just re-did the entire website using Publish (Publish by John Sundell). So, a new hello world post :)

Tagged with:
\ No newline at end of file diff --git a/posts/index.html b/posts/index.html index 06822d3..ae03037 100644 --- a/posts/index.html +++ b/posts/index.html @@ -1 +1 @@ -Posts | Navan Chauhan
Navan Chauhan

Posts

Tips, tricks and tutorials which I think might be useful.

\ No newline at end of file +Posts | Navan Chauhan
Navan Chauhan

Posts

Tips, tricks and tutorials which I think might be useful.

\ No newline at end of file diff --git a/sitemap.xml b/sitemap.xml index 8d11fd5..159f517 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -1 +1 @@ -https://navanchauhan.github.io/aboutdaily1.02020-02-07https://navanchauhan.github.io/postsdaily1.02020-06-01https://navanchauhan.github.io/posts/2010-01-24-experimentsmonthly0.52020-02-04https://navanchauhan.github.io/posts/2019-05-05-Custom-Snowboard-Anemone-Thememonthly0.52020-03-09https://navanchauhan.github.io/posts/2019-12-04-Google-Teachable-Machinesmonthly0.52020-03-09https://navanchauhan.github.io/posts/2019-12-08-Image-Classifier-Tensorflowmonthly0.52020-05-24https://navanchauhan.github.io/posts/2019-12-08-Splitting-Zipsmonthly0.52020-01-18https://navanchauhan.github.io/posts/2019-12-10-TensorFlow-Model-Predictionmonthly0.52020-01-18https://navanchauhan.github.io/posts/2019-12-16-TensorFlow-Polynomial-Regressionmonthly0.52020-01-18https://navanchauhan.github.io/posts/2019-12-22-Fake-News-Detectormonthly0.52020-01-18https://navanchauhan.github.io/posts/2020-01-14-Converting-between-PIL-NumPymonthly0.52020-03-09https://navanchauhan.github.io/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colabmonthly0.52020-01-19https://navanchauhan.github.io/posts/2020-01-16-Image-Classifier-Using-Turicreatemonthly0.52020-01-19https://navanchauhan.github.io/posts/2020-01-19-Connect-To-Bluetooth-Devices-Linux-Terminalmonthly0.52020-01-20https://navanchauhan.github.io/posts/2020-03-03-Playing-With-Android-TVmonthly0.52020-03-10https://navanchauhan.github.io/posts/2020-03-08-Making-Vaporwave-Trackmonthly0.52020-03-08https://navanchauhan.github.io/posts/2020-04-13-Fixing-X11-Error-AmberTools-macOSmonthly0.52020-06-01https://navanchauhan.github.io/posts/2020-05-31-compiling-open-babel-on-iosmonthly0.52020-06-01https://navanchauhan.github.io/posts/2020-06-01-Speeding-Up-Molecular-Docking-Workflow-AutoDock-Vina-and-PyMOLmonthly0.52020-06-01https://navanchauhan.github.io/posts/hello-worldmonthly0.52020-01-04https://navanchauhan.github.io/publicationsdaily1.02020-03-17https://navanchauhan.github.io/publications/2019-05-14-Detecting-Driver-Fatigue-Over-Speeding-and-Speeding-up-Post-Accident-Responsemonthly0.52020-03-14https://navanchauhan.github.io/publications/2020-03-14-generating-vaporwavemonthly0.52020-03-15https://navanchauhan.github.io/publications/2020-03-17-Possible-Drug-Candidates-COVID-19monthly0.52020-03-18 \ No newline at end of file +https://navanchauhan.github.io/aboutdaily1.02020-02-07https://navanchauhan.github.io/postsdaily1.02020-06-01https://navanchauhan.github.io/posts/2010-01-24-experimentsmonthly0.52020-06-01https://navanchauhan.github.io/posts/2019-05-05-Custom-Snowboard-Anemone-Thememonthly0.52020-06-01https://navanchauhan.github.io/posts/2019-12-04-Google-Teachable-Machinesmonthly0.52020-06-01https://navanchauhan.github.io/posts/2019-12-08-Image-Classifier-Tensorflowmonthly0.52020-06-01https://navanchauhan.github.io/posts/2019-12-08-Splitting-Zipsmonthly0.52020-06-01https://navanchauhan.github.io/posts/2019-12-10-TensorFlow-Model-Predictionmonthly0.52020-06-01https://navanchauhan.github.io/posts/2019-12-16-TensorFlow-Polynomial-Regressionmonthly0.52020-06-01https://navanchauhan.github.io/posts/2019-12-22-Fake-News-Detectormonthly0.52020-06-01https://navanchauhan.github.io/posts/2020-01-14-Converting-between-PIL-NumPymonthly0.52020-06-01https://navanchauhan.github.io/posts/2020-01-15-Setting-up-Kaggle-to-use-with-Colabmonthly0.52020-06-01https://navanchauhan.github.io/posts/2020-01-16-Image-Classifier-Using-Turicreatemonthly0.52020-06-01https://navanchauhan.github.io/posts/2020-01-19-Connect-To-Bluetooth-Devices-Linux-Terminalmonthly0.52020-06-01https://navanchauhan.github.io/posts/2020-03-03-Playing-With-Android-TVmonthly0.52020-06-01https://navanchauhan.github.io/posts/2020-03-08-Making-Vaporwave-Trackmonthly0.52020-06-01https://navanchauhan.github.io/posts/2020-04-13-Fixing-X11-Error-AmberTools-macOSmonthly0.52020-06-01https://navanchauhan.github.io/posts/2020-05-31-compiling-open-babel-on-iosmonthly0.52020-06-01https://navanchauhan.github.io/posts/2020-06-01-Speeding-Up-Molecular-Docking-Workflow-AutoDock-Vina-and-PyMOLmonthly0.52020-06-01https://navanchauhan.github.io/posts/hello-worldmonthly0.52020-06-01https://navanchauhan.github.io/publicationsdaily1.02020-03-17https://navanchauhan.github.io/publications/2019-05-14-Detecting-Driver-Fatigue-Over-Speeding-and-Speeding-up-Post-Accident-Responsemonthly0.52020-03-14https://navanchauhan.github.io/publications/2020-03-14-generating-vaporwavemonthly0.52020-03-15https://navanchauhan.github.io/publications/2020-03-17-Possible-Drug-Candidates-COVID-19monthly0.52020-03-18 \ No newline at end of file diff --git a/tags/android/index.html b/tags/android/index.html index b9bdd73..cc393ad 100644 --- a/tags/android/index.html +++ b/tags/android/index.html @@ -1 +1 @@ -Navan Chauhan
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  • Experiments

    🕑 1 minute read. January 24, 2010

    Just a markdown file for all experiments related to the website

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    🕑 1 minute read. January 24, 2010

    Just a markdown file for all experiments related to the website

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