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Hands-On Genetic Algorithms with Python
Hands-On Genetic Algorithms with Python

Hands-On Genetic Algorithms with Python: Applying genetic algorithms to solve real-world deep learning and artificial intelligence problems

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Key benefits

  • Explore the ins and outs of genetic algorithms with this fast-paced guide
  • Implement tasks such as feature selection, search optimization, and cluster analysis using Python
  • Solve combinatorial problems, optimize functions, and enhance the performance of artificial intelligence applications

Description

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.

Who is this book for?

This book is for software developers, data scientists, and AI enthusiasts who want to use genetic algorithms to carry out intelligent tasks in their applications. Working knowledge of Python and basic knowledge of mathematics and computer science will help you get the most out of this book.

What you will learn

  • Understand how to use state-of-the-art Python tools to create genetic algorithm-based applications
  • Use genetic algorithms to optimize functions and solve planning and scheduling problems
  • Enhance the performance of machine learning models and optimize deep learning network architecture
  • Apply genetic algorithms to reinforcement learning tasks using OpenAI Gym
  • Explore how images can be reconstructed using a set of semi-transparent shapes
  • Discover other bio-inspired techniques, such as genetic programming and particle swarm optimization

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jan 31, 2020
Length: 346 pages
Edition : 1st
Language : English
ISBN-13 : 9781838559182
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What do you get with eBook?

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Product feature icon Download this book in EPUB and PDF formats
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Product Details

Publication date : Jan 31, 2020
Length: 346 pages
Edition : 1st
Language : English
ISBN-13 : 9781838559182
Category :
Languages :
Tools :

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Frequently bought together


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Total $ 153.97
Mastering Machine Learning Algorithms
$48.99
Artificial Intelligence with Python
$54.99
Hands-On Genetic Algorithms with Python
$49.99
Total $ 153.97 Stars icon
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Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8
(12 Ratings)
5 star 91.7%
4 star 0%
3 star 8.3%
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1 star 0%
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A. Kashyap Mar 23, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Easy to understand and extremely useful. Helped me out a great deal with a real work project.
Amazon Verified review Amazon
Amazon Customer Jul 16, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This was the best Genetic Algorithm book ever in my life. Due to its simplicity and pesudo-code-like nature of the Python language, the example codes does not interfere with the readers’ intellectual engagement into the beauty of evolutionary algorithms.
Amazon Verified review Amazon
Adam Becker Jun 16, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book has made such a profound impact on our work that it is difficult to remember what things looked like before we picked it up. The content is accessible, well-written, equipped with helpful examples and with beautiful visualizations. I, and the rest of the team, consistently come back to it as reference and guide. Couldn't recommend it more.
Amazon Verified review Amazon
Debanjan & Priyanka Dec 09, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Very thorough, useful and practical introduction to genetic algorithms. Found it better than almost all similar books. It shows a good way to use deap libraries as well.
Amazon Verified review Amazon
Scott M Thompson Mar 03, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The code examples were easy to follow. The author did a nice job of explaining a complex concept in understandable terms. I really enjoyed the book. It helped me gain a better understanding of the use of genetic algorithms.
Amazon Verified review Amazon
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