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Artificial Intelligence and Machine Learning Fundamentals

Artificial Intelligence and Machine Learning Fundamentals

By : Nagy
4.3 (110)
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Artificial Intelligence and Machine Learning Fundamentals

Artificial Intelligence and Machine Learning Fundamentals

4.3 (110)
By: 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 (9 chapters)
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The Fundamentals of Classification


While regression focuses on creating a model that best fits our data to predict the future, classification is all about creating a model that separates our data into separate classes.

Assuming that you have some data belonging to separate classes, classification helps you predict the class a new data point belongs to. A classifier is a model that determines the label value belonging to any data point in the domain. Suppose you have a set of points, P = {p1, p2, p3, ..., pm}, and another set of points, Q = {q1, q2, q3, ..., qn}. You treat these points as members of different classes. For simplicity, we could imagine that P contains credit-worthy individuals, and Q contains individuals that are risky in terms of their credit repayment tendencies.

You can divide the state space so that all points in P are on one cluster of the state space, and then disjoint from the state space cluster containing all points in Q. Once you find these bounded spaces, called clusters...

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