Polynomial Regression Using TensorFlow

In this tutorial you will learn about polynomial regression and how you can implement it in Tensorflow.

@@ -58,19 +58,19 @@

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
@@ -81,9 +81,9 @@ Polynomial regression even fits a non-linear relationship (e.g when the points d

Dataset

Creating Random Data

Even though in this tutorial we will use a Position Vs Salary dataset, it is important to know how to create synthetic data

@@ -105,7 +105,7 @@ Polynomial regression even fits a non-linear relationship (e.g when the points d -

Position vs Salary Dataset

We will be using https://drive.google.com/file/d/1tNL4jxZEfpaP4oflfSn6pIHJX7Pachm9/view (Salary vs Position Dataset)

@@ -160,7 +160,7 @@ Polynomial regression even fits a non-linear relationship (e.g when the points d

Defining Stuff

X = tf.placeholder("float")
@@ -168,7 +168,7 @@ Polynomial regression even fits a non-linear relationship (e.g when the points d

Defining Variables

We first define all the coefficients and constant as tensorflow variables having a random initial value

@@ -182,7 +182,7 @@ Polynomial regression even fits a non-linear relationship (e.g when the points d -

Model Configuration

learning_rate = 0.2
@@ -190,7 +190,7 @@ Polynomial regression even fits a non-linear relationship (e.g when the points d

Equations

deg1 = a*X + b
@@ -201,7 +201,7 @@ Polynomial regression even fits a non-linear relationship (e.g when the points d

Cost Function

We use the Mean Squared Error Function

@@ -214,7 +214,7 @@ Polynomial regression even fits a non-linear relationship (e.g when the points d -

Optimizer

We use the AdamOptimizer for the polynomial functions and GradientDescentOptimizer for the linear function

@@ -232,12 +232,12 @@ Polynomial regression even fits a non-linear relationship (e.g when the points d -

Model Predictions

For each type of equation first we make the model predict the values of the coefficient(s) and constant, once we get these values we use it to predict the Y values using the X values. We then plot it to compare the actual data and predicted line.

Linear Equation

with tf.Session() as sess:
@@ -301,7 +301,7 @@ values using the X values. We then plot it to compare the actual data and predic
 
 
 
-Quadratic Equation
+Quadratic Equation
 
 
 with tf.Session() as sess:
@@ -366,7 +366,7 @@ values using the X values. We then plot it to compare the actual data and predic
 
 
 
-Cubic
+Cubic
 
 
 with tf.Session() as sess:
@@ -432,7 +432,7 @@ values using the X values. We then plot it to compare the actual data and predic
 
 
 
-Quartic
+Quartic
 
 
 with tf.Session() as sess:
@@ -499,7 +499,7 @@ values using the X values. We then plot it to compare the actual data and predic
 
 
 
-Quintic
+Quintic
 
 
 with tf.Session() as sess:
@@ -565,13 +565,13 @@ values using the X values. We then plot it to compare the actual data and predic
 
 
 
-Results and Conclusion
+Results and Conclusion
 
 You just learnt Polynomial Regression using TensorFlow!
 
-Notes
+Notes
 
-Overfitting
+Overfitting
 
 
   
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From 9e620084e57378952c1a7f8e0a772ebebd18932b Mon Sep 17 00:00:00 2001
From: Navan Chauhan 
Date: Wed, 27 Mar 2024 20:35:09 -0600
Subject: quick fix

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 1 file changed, 3 insertions(+), 3 deletions(-)

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@@ -6,13 +6,13 @@
     
     
     
-    id="polynomial-regression-using-tensorflow">Polynomial Regression Using TensorFlow
+    Polynomial Regression Using TensorFlow
     
     
     
-    Polynomial Regression Using TensorFlow" />
-    Polynomial Regression Using TensorFlow" />
+    
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From 01ff93c9c16867216f2d249664803860e1d6d5eb Mon Sep 17 00:00:00 2001
From: Navan Chauhan 
Date: Wed, 27 Mar 2024 22:49:40 -0600
Subject: generate new theme

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 1 file changed, 37 insertions(+), 18 deletions(-)

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+    
+    
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+    Polynomial Regression Using TensorFlow
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-    Polynomial Regression Using TensorFlow
     
     
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 	Polynomial Regression Using TensorFlow
 
 In this tutorial you will learn about polynomial regression and how you can implement it in Tensorflow.
@@ -586,14 +604,15 @@ values using the X values. We then plot it to compare the actual data and predic
 
 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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From de19543d7fb44d343b052dc9b34ede78620c4a46 Mon Sep 17 00:00:00 2001
From: Navan Chauhan 
Date: Wed, 27 Mar 2024 23:36:55 -0600
Subject: Generate

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+++ b/docs/posts/2019-12-16-TensorFlow-Polynomial-Regression.html
@@ -46,7 +46,7 @@
     
         
             Navan
-            Something Funny
+            Alea iacta est.
         
 
         
@@ -56,9 +56,21 @@
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             colophon
         
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+        
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From a982ceab0b45609991179b3020a00260eed6f798 Mon Sep 17 00:00:00 2001
From: Navan Chauhan 
Date: Wed, 27 Mar 2024 23:45:59 -0600
Subject: css

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     Polynomial Regression Using TensorFlow
 
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