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    Hands-On Genetic Algorithms with Python. Apply genetic algorithms to solve real-world AI and machine learning problems - Second Edition Eyal Wirsansky

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Hands-On Genetic Algorithms with Python. Apply genetic algorithms to solve real-world AI and machine learning problems - Second Edition Eyal Wirsansky - okladka książki

    Hands-On Genetic Algorithms with Python. Apply genetic algorithms to solve real-world AI and machine learning problems - Second Edition Eyal Wirsansky - okladka książki

    Hands-On Genetic Algorithms with Python. Apply genetic algorithms to solve real-world AI and machine learning problems - Second Edition Eyal Wirsansky - audiobook MP3

    Hands-On Genetic Algorithms with Python. Apply genetic algorithms to solve real-world AI and machine learning problems - Second Edition Eyal Wirsansky - audiobook CD

    Autor:
    Eyal Wirsansky
    Serie wydawnicze:
    Hands-on
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    418
    Dostępne formaty:
         PDF
         ePub
    Written by Eyal Wirsansky, a senior data scientist and AI researcher with over 25 years of experience and a research background in genetic algorithms and neural networks, Hands-On Genetic Algorithms with Python offers expert insights and practical knowledge to master genetic algorithms.
    After an introduction to genetic algorithms and their principles of operation, you’ll find out how they differ from traditional algorithms and the types of problems they can solve, followed by applying them to search and optimization tasks such as planning, scheduling, gaming, and analytics. As you progress, you’ll delve into explainable AI and apply genetic algorithms to AI to improve machine learning and deep learning models, as well as tackle reinforcement learning and NLP tasks. This updated second edition further expands on applying genetic algorithms to NLP and XAI and speeding up genetic algorithms with concurrency and cloud computing. You’ll also get to grips with the NEAT algorithm. The book concludes with an image reconstruction project and other related technologies for future applications.
    By the end of this book, you’ll have gained hands-on experience in applying genetic algorithms across a variety of fields, with emphasis on artificial intelligence with Python.

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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.

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