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The Applied Artificial Intelligence Workshop

You're reading from   The Applied Artificial Intelligence Workshop Start working with AI today, to build games, design decision trees, and train your own machine learning models

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781800205819
Length 420 pages
Edition 1st Edition
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Authors (3):
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Anthony So Anthony So
Author Profile Icon Anthony So
Anthony So
Zsolt Nagy Zsolt Nagy
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Zsolt Nagy
William So William So
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William So
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Toc

Table of Contents (8) Chapters Close

Preface
1. Introduction to Artificial Intelligence 2. An Introduction to Regression FREE CHAPTER 3. An Introduction to Classification 4. An Introduction to Decision Trees 5. Artificial Intelligence: Clustering 6. Neural Networks and Deep Learning Appendix

Introduction

In the previous chapter, you were introduced to the fundamentals of Artificial Intelligence (AI), which helped you create the game Tic-Tac-Toe. In this chapter, we will be looking at regression, which is a machine learning algorithm that can be used to measure how closely related independent variable(s), called features, relate to a dependent variable called a label.

Linear regression is a concept with many applications a variety of fields, ranging from finance (predicting the price of an asset) to business (predicting the sales of a product) and even the economy (predicting economy growth).

Most of this chapter will deal with different forms of linear regression, including linear regression with one variable, linear regression with multiple variables, polynomial regression with one variable, and polynomial regression with multiple variables. Python provides lots of forms of support for performing regression operations and we will also be looking at these later on...

You have been reading a chapter from
The Applied Artificial Intelligence Workshop
Published in: Jul 2020
Publisher: Packt
ISBN-13: 9781800205819
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