Hands-On Genetic Algorithms with Python

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By Eyal Wirsansky
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    Section 1: The Basics of Genetic Algorithms

About this book

Genetic algorithms are a family of search, optimization, and learning algorithms inspired by the principles of natural evolution. By imitating the evolutionary process, genetic algorithms can overcome hurdles encountered in traditional search algorithms and provide high-quality solutions for a variety of problems. This book will help you get to grips with a powerful yet simple approach to applying genetic algorithms to a wide range of tasks using Python, covering the latest developments in artificial intelligence.

After introducing you to genetic algorithms and their principles of operation, you'll understand how they differ from traditional algorithms and what types of problems they can solve. You'll then discover how they can be applied to search and optimization problems, such as planning, scheduling, gaming, and analytics. As you advance, you'll also learn how to use genetic algorithms to improve your machine learning and deep learning models, solve reinforcement learning tasks, and perform image reconstruction. Finally, you'll cover several related technologies that can open up new possibilities for future applications.

By the end of this book, you'll have hands-on experience of applying genetic algorithms in artificial intelligence as well as in numerous other domains.

Publication date:
January 2020


Section 1: The Basics of Genetic Algorithms

In this section, you will be introduced to the key concepts of genetic algorithms and how they can be used.

This section comprises the following chapters:

  • Chapter 1, An Introduction to Genetic Algorithms
  • Chapter 2, Understanding the Key Components of Genetic Algorithms

About the Author

  • Eyal Wirsansky

    Eyal Wirsansky is a senior software engineer, a technology community leader, and an artificial intelligence enthusiast and researcher. Eyal started his software engineering career as a pioneer in the field of voice over IP, and he now has over 20 years' experience of creating a variety of high-performing enterprise solutions. While in graduate school, he focused his research on genetic algorithms and neural networks. One outcome of his research is a novel supervised machine learning algorithm that combines the two. Eyal leads the Jacksonville (FL) Java user group, hosts the Artificial Intelligence for Enterprise virtual user group, and writes the developer-oriented artificial intelligence blog, ai4java.

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