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

Summary


In this course, we have learned about the fundamentals of AI and applications of AI in lesson on principles of AI, then we wrote a Python code to model a Tic-Tac-Toe game.

In the lesson AI with Search Techniques and Games, we solved the Tic-Tac-Toe game with game AI tools and search techniques. We learned about the search algorithms of Breadth First Search and Depth First Search. The A* algorithm helped students model a pathfinding problem. The lesson was concluded with modeling multiplayer games.

In the next couple of lessons, we learned about supervised learning using regression and classification. These lessons included data preprocessing, train-test splitting, and models that were used in several real-life scenarios. Linear regression, polynomial regression, and Support Vector Machines all came in handy when it came to predicting stock data. Classification was performed using the k-nearest neighbor and Support Vector classifiers. Several activities helped students apply the basics...