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.
Test your code and get inspired to try new problems. Work through scenarios to code your way out of a paper bag; an important skill for any competent programmer. See how the algorithms explore and learn by creating visualizations of each problem. Get inspired to design your own machine learning projects and become familiar with the jargon.
What You Need:
|Publisher:||Pragmatic Programmers, LLC, The|
|Product dimensions:||7.50(w) x 9.25(h) x (d)|
About the Author
Frances Buontempo is the editor of ACCU's Overload magazine (https://accu.org/index.php/journal/overload_by_cover). She has published articles and given talks centered on technology and machine learning. With a PhD in data mining, she has been programming professionally since the 1990s. During her career as a programmer, she has championed unit testing, mentored newer developers, deleted quite a bit of code and fixed a variety of bugs.