Hands-On Genetic Algorithms with Python
Using this book, you will gain expertise in genetic algorithms, understand how they work and know when and how to use them to create intelligent Python-based applications. By the end of this book, you will have hands-on experience applying genetic algorithms to artificial intelligence as well as numerous other domains.
Offered by
Difficulty Level
Intermediate
Completion Time
11h32m
Language
English
About Book
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.
Hands-On Genetic Algorithms with Python
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 11h32m total length
An Introduction to Genetic Algorithms
Understanding the Key Components of Genetic Algorithms
Using the DEAP Framework
Combinatorial Optimization
Constraint Satisfaction
Optimizing Continuous Functions
Enhancing Machine Learning Models Using Feature Selection
Hyperparameter Tuning Machine Learning Models
Architecture Optimization of Deep Learning Networks
Reinforcement Learning with Genetic Algorithms
Genetic Image Reconstruction
Other Evolutionary and Bio-Inspired Computation Techniques
Related Resources
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