Effective XGBoost Tuning, Understanding, and Deploying Classification Models (Grayscale Indian Edition)
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Effective XGBoost Tuning, Understanding, and Deploying Classification Models (Grayscale Indian Edition) (Paperback, Matt Harrison)

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Effective XGBoost Tuning, Understanding, and Deploying Classification Models (Grayscale Indian Edition)  (Paperback, Matt Harrison)

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    Highlights
    • Binding: Paperback
    • Publisher: Shroff/MetaSnake
    • Genre: Computing & Information Technology
    • ISBN: 9789355424112, 9355424116
    • Edition: First, 2023
    • Pages: 220
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  • Description
    All Indian Reprints of Metasnake are Printed in Grayscale. ""Effective XGBoost"" is the ultimate guide to mastering the art of classification. Whether you're a seasoned data scientist or just starting out, this comprehensive book will take you from the basics of XGBoost to advanced techniques for optimizing, tuning, understanding, and deploying your models. XGBoost is one of the most popular machine learning algorithms used in data science today. With its ability to handle large datasets, handle missing values, and deal with non-linear relationships, it has become an essential tool for many data scientists. In this book, you'll learn everything you need to know to become an expert in XGBoost.
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    Imprint
    • SPD
    Publication Year
    • 2023 45041
    Contributors
    Author Info
    • Matt Harrison runs MetaSnake, a Python and Data Science consultancy and corporate training shop. In the past, he has worked across the domains of search, build management and testing, business intelligence, and storage. He has presented and taught tutorials at conferences such as Strata, SciPy, SCALE, PyCON, and OSCON as well as local user conferences. The structure and content of his books are based on first-hand experience teaching Python to many individuals.
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    Weight
    • 400
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