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Sean Moriarity Genetic Algorithms in Elixir (Paperback)

Sean Moriarity Genetic Algorithms in Elixir (Paperback)
$66.13

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Further Details

Title: Genetic Algorithms in Elixir
Condition: New
Author: Sean Moriarity
Format: Paperback
ISBN-10: 168050794X
EAN: 9781680507942
ISBN: 9781680507942
Publisher: The Pragmatic Programmers
Genre: Computing & Internet
Release Date: 04/08/2021
Description:

From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications. But you don\'t need an exotic new language or framework to get started; you can learn about genetic algorithms in a language you\'re already familiar with. Join us for an in-depth look at the algorithms, techniques, and methods that go into writing a genetic algorithm. From introductory problems to real-world applications, you\'ll learn the underlying principles of problem solving using genetic algorithms.

Evolutionary algorithms are a unique and often overlooked subset of machine learning and artificial intelligence. Because of this, most of the available resources are outdated or too academic in nature, and none of them are made with Elixir programmers in mind.

Start from the ground up with genetic algorithms in a language you are familiar with. Discover the power of genetic algorithms through simple solutions to challenging problems. Use Elixir features to write genetic algorithms that are concise and idiomatic. Learn the complete life cycle of solving a problem using genetic algorithms. Understand the different techniques and fine-tuning required to solve a wide array of problems. Plan, test, analyze, and visualize your genetic algorithms with real-world applications.

Open your eyes to a unique and powerful field - without having to learn a new language or framework.

What You Need:

You\'ll need a macOS, Windows, or Linux distribution with an up-to-date Elixir installation.


Language: English
Country/Region of Manufacture: US
Item Height: 235mm
Item Length: 190mm
Item Width: 14mm
Item Weight: 450g
Release Year: 2021

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