Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Hands-On Genetic Algorithms with Python
  • Table Of Contents Toc
Hands-On Genetic Algorithms with Python

Hands-On Genetic Algorithms with Python

By : Eyal Wirsansky
4.8 (12)
close
close
Hands-On Genetic Algorithms with Python

Hands-On Genetic Algorithms with Python

4.8 (12)
By: Eyal Wirsansky

Overview of 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.
Table of Contents (18 chapters)
close
close
1
Section 1: The Basics of Genetic Algorithms
4
Section 2: Solving Problems with Genetic Algorithms
9
Section 3: Artificial Intelligence Applications of Genetic Algorithms
14
Section 4: Related Technologies

Using the creator module

The first powerful tool provided by the DEAP framework is the creator module. The creator module is used as a meta-factory, and it enables us to extend existing classes by augmenting them with new attributes.

For example, suppose we have a class called Employee. Using the creator tool, we can extend the Employee class by creating a Developer class as follows:

from deap import creator
creator.create("Developer", Employee, position = "Developer", programmingLanguages = set)

The first argument passed to the create() function is the desired name for the new class. The second argument is the existing class to be extended. Then, each additional argument defines an attribute for the new class. If the argument is assigned a class (such as a dict or a set), it will be added to the new class as an instant attribute initialized in the constructor...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Hands-On Genetic Algorithms with Python
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon