Genetic Algorithms and Machine Learning for Programmers: Create AI Models and Evolve Solutions
Description
(Pragmatic Programmers) 1st Edition
by Frances Buontempo (Author)
Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you.
Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems.
In this book, you will:
- Use heuristics and design fitness functions.
- Build genetic algorithms.
- Make nature-inspired swarms with ants, bees and particles.
- Create Monte Carlo simulations.
- Investigate cellular automata.
- Find minima and maxima, using hill climbing and simulated annealing.
- Try selection methods, including tournament and roulette wheels.
- Learn about heuristics, fitness functions, metrics, and clusters.
