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Genetic algorithms and machine learning for programmers : create AI models and evolve solutions /

Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to machine learning. Discover machine learning algorithms using a handful of self-contained recipes. Create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, and cel...

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Bibliographic Details
Main Authors: Buontempo, Frances
Published: The Pragmatic Bookshelf,
Publisher Address: Raleigh, North Carolina :
Publication Dates: [2019]
Literature type: Book
Language: English
Series: The pragmatic programmers
Subjects:
Genetic algorithms
Genetic programming Computer science
Machine learning
Artificial intelligence
Summary: Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to machine learning. Discover machine learning algorithms using a handful of self-contained recipes. Create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, and cellular automata. Find minima and maxima, using hill climbing and simulated annealing. Try selection mathods, including tournament and roulette wheels. Learn about heuristics, fitness functions, metrics, and clusters.
Carrier Form: viii, 218 pages : illustrations ; 24 cm.
Bibliography: Includes bibliographical and references (page [207]) and index.
ISBN: 9781680506204
168050620X
Index Number: QA76
CLC: TP181
TP311.1
TP301.6
Call Number: TP301.6/B944
Contents: Escape! Code your way out of a paper bag -- Decide! Find the paper bag -- Boom! Create a genetic algorithm -- Swarm! Build a nature-inspired swarm -- Colonize! Discover pathways -- Diffuse! Employ a stochastic model -- Buzz! Converge on one solution -- Alive! Create artificial life -- Dream! Explore CA with GA -- Optimize! Find the best.

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