Before you leave...
Take 20% off your first order
20% off
Enter the code below at checkout to get 20% off your first order
Discover summer reading lists for all ages & interests!
Find Your Next Read

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:
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:
Code in C++ (>= C++11), Python (2.x or 3.x) and JavaScript (using the HTML5 canvas). Also uses matplotlib and some open source libraries, including SFML, Catch and Cosmic-Ray. These plotting and testing libraries are not required but their use will give you a fuller experience. Armed with just a text editor and compiler/interpreter for your language of choice you can still code along from the general algorithm descriptions.
Author: Frances Buontempo
ISBN-10: 168050620X
ISBN-13: 9781680506204
Publisher: Pragmatic Bookshelf
Language: English
Published: 02/26/2019
Pages: 236
Format: Paperback
Weight: 0.91lbs
Size: 9.25h x 7.50w x 0.50d
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.
Thanks for subscribing!
This email has been registered!
Take 20% off your first order
Enter the code below at checkout to get 20% off your first order