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    Hands-On Genetic Algorithms With Python. Apply genetic algorithms to solve real-world, artificial intelligence and machine learning problems - Second Edition

    (ebook) (audiobook) (audiobook) Książka w języku angielskim
    Autor:
    Eyal Wirsansky
    Hands-On Genetic Algorithms With Python. Apply genetic algorithms to solve real-world, artificial intelligence and machine learning problems - Second Edition Eyal Wirsansky - okladka książki

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

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

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

    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Genetic algorithms are a family of search, optimization, and learning algorithms inspired by the principles of natural evolution. This book will guide you through mastering the powerful, yet simple technique of genetic algorithms, applying them to a wide range of tasks and using them in artificial intelligence applications, all with Python.
    After introducing genetic algorithms and their principles of operation, you will find out how they differ from traditional algorithms and the types of problems they can solve. Discover how they can be applied to search and optimization problems, such as planning, scheduling, gaming, and analytics. Learn to apply genetic algorithms to artificial intelligence - to improve machine learning and deep learning models, solve reinforcement learning as well as natural language processing tasks, and delve into explainable AI. The new edition expands on applying genetic algorithms to NLP and XAI, speeding up genetic algorithms with concurrency and cloud computing, and understanding the NEAT algorithm. The book concludes with an image reconstruction project, followed by demonstrations of related technologies, for future applications.
    By the end of this book, you will have gained hands-on experience in applying genetic algorithms across a variety of fields, with emphasis on artificial intelligence.

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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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