From 284ec747d2ac0de55c3859283c7f6d63451b0480 Mon Sep 17 00:00:00 2001
From: Navan Chauhan <navanchauhan@gmail.com>
Date: Sat, 21 Oct 2023 00:44:42 -0600
Subject: fix canonical url

---
 docs/posts/2019-12-16-TensorFlow-Polynomial-Regression.html | 13 +++++--------
 1 file changed, 5 insertions(+), 8 deletions(-)

(limited to 'docs/posts/2019-12-16-TensorFlow-Polynomial-Regression.html')

diff --git a/docs/posts/2019-12-16-TensorFlow-Polynomial-Regression.html b/docs/posts/2019-12-16-TensorFlow-Polynomial-Regression.html
index 51c31d8..a34dcbf 100644
--- a/docs/posts/2019-12-16-TensorFlow-Polynomial-Regression.html
+++ b/docs/posts/2019-12-16-TensorFlow-Polynomial-Regression.html
@@ -8,9 +8,9 @@
     <meta name="viewport" content="width=device-width, initial-scale=1.0">
     <title>Polynomial Regression Using TensorFlow</title>
     <meta name="og:site_name" content="Navan Chauhan" />
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-    <meta name="twitter:url" content="https://web.navan.dev/" />
-    <meta name="og:url" content="https://web.navan.dev/" />
+    <link rel="canonical" href="https://web.navan.dev/posts/2019-12-16-TensorFlow-Polynomial-Regression.html" />
+    <meta name="twitter:url" content="https://web.navan.dev/posts/2019-12-16-TensorFlow-Polynomial-Regression.html />
+    <meta name="og:url" content="https://web.navan.dev/posts/2019-12-16-TensorFlow-Polynomial-Regression.html" />
     <meta name="twitter:title" content="Polynomial Regression Using TensorFlow" />
     <meta name="og:title" content="Polynomial Regression Using TensorFlow" />
     <meta name="description" content="Polynomial regression using TensorFlow" />
@@ -22,7 +22,6 @@
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@@ -586,15 +585,13 @@ values using the X values. We then plot it to compare the actual data and predic
 <p>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</p>
 
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+	<script data-isso="https://comments.navan.dev/"
+        src="https://comments.navan.dev/js/embed.min.js"></script>
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