Ultimate Genetic Algorithms with Python

Harness Genetic Algorithms to Build the Next Generation of Adaptive AI.Book DescriptionGenetic Algorithms (GAs) are nature-inspired optimization tools that help AI systems adapt, improve, and solve complex problems efficiently. Ultimate Genetic Algorithms with Python explains elaborately the fundamentals of GAs to practical, Python-based implementation, using PyGAD and DEAP.The book starts with a solid foundation, explaining how evolutionary principles can be applied to optimization tasks, search problems, and model improvement.You will also explore GA applications across multiple AI domains: optimizing machine learning workflows, evolving neural network architectures in deep learning, enhancing feature selection in NLP, improving performance in computer vision, and guiding exploration strategies in reinforcement learning. Each application chapter includes step-by-step coding examples, performance comparisons, and tuning techniques.Table of Contents1. Introduction to Genetic Algorithms2. Fundamentals of Genetic Algorithms3. Overview of Genetic Algorithm Libraries4. Genetic Algorithms and Their Applications5. Foundation of Evolutionary Algorithms6. Advanced Evolutionary Algorithms7. Metaheuristic Optimization Algorithms8. Application of Evolutionary Algo (GAs) and Generative Agentic AI9. Applying Genetic Algorithm to Machine Learning10. Applying Deep Learning to Genetic Algorithm11. Applying Computer Vision Application to Genetic Algorithms12. Applying NLP to Genetic Algorithms13. Applying Reinforcement Learning to Genetic Algorithms14. The Future of Genetic AlgorithmsIndex