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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 f42d4a2..06e7974 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 @@ -<!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/2019-12-16-TensorFlow-Polynomial-Regression"/><meta name="twitter:url" content="https://navanchauhan.github.io/posts/2019-12-16-TensorFlow-Polynomial-Regression"/><meta name="og:url" content="https://navanchauhan.github.io/posts/2019-12-16-TensorFlow-Polynomial-Regression"/><title>Polynomial Regression Using TensorFlow | Navan Chauhan</title><meta name="twitter:title" content="Polynomial Regression Using TensorFlow | Navan Chauhan"/><meta name="og:title" content="Polynomial Regression Using TensorFlow | Navan Chauhan"/><meta name="description" content="Polynomial regression using TensorFlow"/><meta name="twitter:description" content="Polynomial regression using TensorFlow"/><meta name="og:description" content="Polynomial regression using TensorFlow"/><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="/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">🕑 16 minute read.</span><h1>Polynomial Regression Using TensorFlow</h1><p><strong>In this tutorial you will learn about polynomial regression and how you can implement it in Tensorflow.</strong></p><p>In this, we will be performing polynomial regression using 5 types of equations -</p><ul><li>Linear</li><li>Quadratic</li><li>Cubic</li><li>Quartic</li><li>Quintic</li></ul><h2>Regression</h2><h3>What is Regression?</h3><p>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 ).</p><h3>What is Polynomial Regression</h3><p>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).</p><h2>Imports</h2><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">tensorflow.compat.v1</span> <span class="kn">as</span> <span class="nn">tf</span> +<!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/2019-12-16-TensorFlow-Polynomial-Regression"/><meta name="twitter:url" content="https://navanchauhan.github.io/posts/2019-12-16-TensorFlow-Polynomial-Regression"/><meta name="og:url" content="https://navanchauhan.github.io/posts/2019-12-16-TensorFlow-Polynomial-Regression"/><title>Polynomial Regression Using TensorFlow | Navan Chauhan</title><meta name="twitter:title" content="Polynomial Regression Using TensorFlow | Navan Chauhan"/><meta name="og:title" content="Polynomial Regression Using TensorFlow | Navan Chauhan"/><meta name="description" content="Polynomial regression using TensorFlow"/><meta name="twitter:description" content="Polynomial regression using TensorFlow"/><meta name="og:description" content="Polynomial regression using TensorFlow"/><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">🕑 16 minute read.</span><h1>Polynomial Regression Using TensorFlow</h1><p><strong>In this tutorial you will learn about polynomial regression and how you can implement it in Tensorflow.</strong></p><p>In this, we will be performing polynomial regression using 5 types of equations -</p><ul><li>Linear</li><li>Quadratic</li><li>Cubic</li><li>Quartic</li><li>Quintic</li></ul><h2>Regression</h2><h3>What is Regression?</h3><p>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 ).</p><h3>What is Polynomial Regression</h3><p>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).</p><h2>Imports</h2><pre><code><div class="highlight"><span></span><span class="kn">import</span> <span class="nn">tensorflow.compat.v1</span> <span class="kn">as</span> <span class="nn">tf</span> <span class="n">tf</span><span class="o">.</span><span class="n">disable_v2_behavior</span><span class="p">()</span> <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span> <span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span> |