Hands-On Genetic Algorithms With Python. Apply genetic algorithms to solve real-world, artificial intelligence and machine learning problems - Second Edition

Genetic algorithms are a family of search, optimization, and learning algorithms inspired by the principles of natural evolution. This book will guide you through mastering the powerful, yet simple technique of genetic algorithms, applying them to a wide range of tasks and using them in artificial intelligence applications, all with Python.
After introducing genetic algorithms and their principles of operation, you will find out how they differ from traditional algorithms and the types of problems they can solve. Discover how they can be applied to search and optimization problems, such as planning, scheduling, gaming, and analytics. Learn to apply genetic algorithms to artificial intelligence - to improve machine learning and deep learning models, solve reinforcement learning as well as natural language processing tasks, and delve into explainable AI. The new edition expands on applying genetic algorithms to NLP and XAI, speeding up genetic algorithms with concurrency and cloud computing, and understanding the NEAT algorithm. The book concludes with an image reconstruction project, followed by demonstrations of related technologies, for future applications.
By the end of this book, you will have gained hands-on experience in applying genetic algorithms across a variety of fields, with emphasis on artificial intelligence.