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In den WarenkorbZustand: New. In.
Verlag: Springer International Publishing, 2024
ISBN 10: 3031333446 ISBN 13: 9783031333446
Sprache: Englisch
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is meant as a textbook for undergraduate and graduate students who are willing to understand essential elements of machine learning from both a theoretical and a practical perspective. The choice of the topics in the book is made based on one criterion: whether the practical utility of a certain method justifies its theoretical elaboration for students with a typical mathematical background in engineering and other quantitative fields. As a result, not only does the book contain practically useful techniques, it also presents them in a mathematical language that is accessible to both graduate and advanced undergraduate students.The textbook covers a range of topics including nearest neighbors, linear models, decision trees, ensemble learning, model evaluation and selection,dimensionality reduction, assembling various learning stages, clustering, and deep learning along with an introduction to fundamental Python packages for data science and machine learning such as NumPy, Pandas, Matplotlib, Scikit-Learn, XGBoost, and Keras with TensorFlow backend.Given the current dominant role of the Python programming language for machine learning, the book complements the theoretical presentation of each technique by its Python implementation. In this regard, two chapters are devoted to cover necessary Python programming skills. This feature makes the book self-sufficient for students with different programming backgrounds and is in sharp contrast with other books in the field that assume readers have prior Python programming experience. As such, the systematic structure of the book, along with the many examples and exercises presented, will help the readers to better grasp the content and be equipped with the practical skills required in day-to-day machine learning applications.
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Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
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Anbieter: GreatBookPrices, Columbia, MD, USA
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In den WarenkorbZustand: New.
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In den WarenkorbZustand: As New. Unread book in perfect condition.
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In den WarenkorbZustand: New.
Verlag: Springer International Publishing, 2023
ISBN 10: 3031333411 ISBN 13: 9783031333415
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 96,29
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In den WarenkorbBuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is meant as a textbook for undergraduate and graduate students who are willing to understand essential elements of machine learning from both a theoretical and a practical perspective. The choice of the topics in the book is made based on one criterion: whether the practical utility of a certain method justifies its theoretical elaboration for students with a typical mathematical background in engineering and other quantitative fields. As a result, not only does the book contain practically useful techniques, it also presents them in a mathematical language that is accessible to both graduate and advanced undergraduate students.The textbook covers a range of topics including nearest neighbors, linear models, decision trees, ensemble learning, model evaluation and selection,dimensionality reduction, assembling various learning stages, clustering, and deep learning along with an introduction to fundamental Python packages for data science and machine learning such as NumPy, Pandas, Matplotlib, Scikit-Learn, XGBoost, and Keras with TensorFlow backend.Given the current dominant role of the Python programming language for machine learning, the book complements the theoretical presentation of each technique by its Python implementation. In this regard, two chapters are devoted to cover necessary Python programming skills. This feature makes the book self-sufficient for students with different programming backgrounds and is in sharp contrast with other books in the field that assume readers have prior Python programming experience. As such, the systematic structure of the book, along with the many examples and exercises presented, will help the readers to better grasp the content and be equipped with the practical skills required in day-to-day machine learning applications.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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In den WarenkorbZustand: New. In.
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Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
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In den WarenkorbZustand: As New. Unread book in perfect condition.
Verlag: Springer-Nature New York Inc, 2023
ISBN 10: 3031333411 ISBN 13: 9783031333415
Sprache: Englisch
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 143,84
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In den WarenkorbHardcover. Zustand: Brand New. 469 pages. 9.25x6.10x1.22 inches. In Stock.
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
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