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    Hands-On Genetic Algorithms with Python. Applying genetic algorithms to solve real-world deep learning and artificial intelligence problems Eyal Wirsansky

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Hands-On Genetic Algorithms with Python. Applying genetic algorithms to solve real-world deep learning and artificial intelligence problems Eyal Wirsansky - okladka książki

    Hands-On Genetic Algorithms with Python. Applying genetic algorithms to solve real-world deep learning and artificial intelligence problems Eyal Wirsansky - okladka książki

    Hands-On Genetic Algorithms with Python. Applying genetic algorithms to solve real-world deep learning and artificial intelligence problems Eyal Wirsansky - audiobook MP3

    Hands-On Genetic Algorithms with Python. Applying genetic algorithms to solve real-world deep learning and artificial intelligence problems Eyal Wirsansky - audiobook CD

    Autor:
    Eyal Wirsansky
    Serie wydawnicze:
    Learning
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    346
    Dostępne formaty:
         PDF
         ePub
         Mobi
    Genetic algorithms are a family of search, optimization, and learning algorithms inspired by the principles of natural evolution. By imitating the evolutionary process, genetic algorithms can overcome hurdles encountered in traditional search algorithms and provide high-quality solutions for a variety of problems. This book will help you get to grips with a powerful yet simple approach to applying genetic algorithms to a wide range of tasks using Python, covering the latest developments in artificial intelligence.
    After introducing you to genetic algorithms and their principles of operation, you'll understand how they differ from traditional algorithms and what types of problems they can solve. You'll then discover how they can be applied to search and optimization problems, such as planning, scheduling, gaming, and analytics. As you advance, you'll also learn how to use genetic algorithms to improve your machine learning and deep learning models, solve reinforcement learning tasks, and perform image reconstruction. Finally, you'll cover several related technologies that can open up new possibilities for future applications.
    By the end of this book, you'll have hands-on experience of applying genetic algorithms in artificial intelligence as well as in numerous other domains.

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    O autorze książki

    Eyal Wirsansky is a senior data scientist, an experienced software engineer, a technology community leader, and an artificial intelligence researcher.
    Eyal began his software engineering career over twenty-five years ago as a pioneer in the field of Voice over IP. He currently works as a member of the data platform team at Gradle, Inc.
    During his graduate studies, he focused his research on genetic algorithms and neural networks. A notable result of this research is a novel supervised machine learning algorithm that integrates both approaches.
    In addition to his professional roles, Eyal serves as an adjunct professor at Jacksonville University, where he teaches a class on artificial intelligence. He also leads both the Jacksonville, Florida Java User Group and the Artificial Intelligence for Enterprise virtual user group, and authors the developer-focused artificial intelligence blog, ai4java.

    Zobacz pozostałe książki z serii Learning

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