Genetic Algorithms and Machine Learning for Programmers: Create AI Models and Evolve Solutions

Book Description

Self-driving cars, recognition, and online recommendation engines are all possible thanks to . 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 , 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 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 and become familiar with the jargon.

What You Need:

Code in C++ (>= C++11), Python (2.x or 3.x) and JavaScript (using the canvas). Also uses matplotlib and some open source libraries, including SFML, Catch and Cosmic-Ray. These plotting and 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.

Book Details

  • Title: Genetic Algorithms and Machine Learning for Programmers: Create AI Models and Evolve Solutions
  • Author:
  • Length: 236 pages
  • Edition: 1
  • Language: English
  • Publisher:
  • Publication Date: 2019-02-02
  • ISBN-10: 168050620X
  • ISBN-13: 9781680506204
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