Hands-On Genetic Algorithms with Python

Table of Contents

1. An Introduction to Genetic Algorithms
2. Understanding the Key Components of Genetic Algorithms
3. Using the DEAP Framework
4. Combinatorial Optimization
5. Constraint Satisfaction
6. Optimizing Continuous Functions
7. Enhancing Machine Learning Models Using Feature Selection
8. Hyperparameter Tuning Machine Learning Models
9. Architecture Optimization of Deep Learning Networks
10. Reinforcement Learning with Genetic Algorithms
11. Natural Language Processing
12. Explainable AI and Counterfactuals
13. Speeding Up Genetic Algorithms with Concurrency
14. Harnessing the Cloud
15. Genetic Image Reconstruction
16. Other Evolutionary and Bio-Inspired Computation Techniques