Book Image

Artificial Intelligence and Machine Learning Fundamentals

By : Zsolt Nagy
Book Image

Artificial Intelligence and Machine Learning Fundamentals

By: Zsolt Nagy

Overview of this book

Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills!
Table of Contents (10 chapters)
Artificial Intelligence and Machine Learning Fundamentals
Preface

Chapter 3. Regression

Note

Learning Objectives

By the end of this lesson, you will be able to:

  • Describe the mathematical logic involved in regression

  • Illustrate the use of the NumPy library for Regression

  • Identify linear regression with one variable and with multiple variables

  • Use sswpolynomial regression

Note

This lesson covers the fundamentals of linear and polynomial regression.