Genetic Algorithms and Machine Learning for Programmers: Create AI Models and Ev

Description: Genetic Algorithms and Machine Learning for Programmers by Frances Buontempo 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: 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. FORMAT Paperback LANGUAGE English CONDITION Brand New Author Biography Frances Buontempo is the editor of ACCUs Overload magazine 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. Details ISBN168050620X Author Frances Buontempo Publisher The Pragmatic Programmers Year 2019 ISBN-10 168050620X ISBN-13 9781680506204 Format Paperback Imprint The Pragmatic Programmers Place of Publication Raleigh Country of Publication United States DEWEY 006.31 Short Title Genetic Algorithms and Machine Learning for Programmers Language English Subtitle Create AI Models and Evolve Solutions Pages 236 Illustrations Illustrations, black and white AU Release Date 2019-02-08 NZ Release Date 2019-02-08 Edited by Fu-Chan Wei Birth 1945 Affiliation Consultant Urological Surgeon, Royal Bournemouth Hospital, and Visiting Professor, Bournemouth University, Bournemouth, UK Position Contributor Qualifications MD UK Release Date 2019-02-12 Publication Date 2019-02-26 US Release Date 2019-02-26 Series Pragmatic Programmers Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:123727976;

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