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Practical Artificial Intelligence in Julia: Implementing Neural Networks, Genetic Algorithms, and Neuroevolution in Julia
Bergel, Alexandre (Author) · Springer, Berlin · Paperback
Develop a thorough grasp of artificial intelligence through practical implementations in Julia with "Practical Artificial Intelligence in Julia: Implementing Neural Networks, Genetic Algorithms, and Neuroevolution." This trailblazing book covers classical AI algorithms and provides practical implementations of agile AI applications, highlighting Julia's versatility and high-performance capabilities for AI development.
This book takes on a practical approach to ensure that readers translate theoretical concepts into tangible, real-world scenarios. Along the way, you will learn and implement from scratch neural networks, genetic algorithms, and neuroevolution. Author Dr. Alexandre Bergel uses practical examples, such as solutions to the traveling sales problem and a fun MarioBro-like game (including a random level generator) to reinforce AI techniques. Meanwhile, the book introduces Darwinian evolution principles, demonstrating how to evolve zoomorphic organisms to solve particular tasks, such as stair climbing or going over obstacles.
This book stands out as among the earliest to delve into Generative Algorithms and Neuroevolutions in Julia, and it is one of the few available that offers a comprehensive implementation of Neuroevolution. It is equally as fun as it is informative, providing readers with source code to play along with and apply to future projects.
What You Will Learn:
Solve simple classification tasks using neural networksUse generative algorithms to solve complex algorithmic problemsApply Darwinian evolution principles to evolve artificially living creaturesDiscover how to Neuroevolution to build an artificial player to solve a MarioBros-like game
Who This Book is For:
This book is written for software engineers, programmers and developers who are eager to gain practical insights into AI implementation using Julia at a beginner/intermediate level
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