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Machine Learning: The Basics (Machine Learning: Foundations, Methodologies, and Applications)
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Machine Learning: The Basics (Machine Learning: Foundations, Methodologies, and Applications)
To make optimal use of ML, it is essential to understand its underlying principles.
Machine Learning: The Basics (Machine Learning: Foundations, Methodologies, and Applications)
物品 #: 52260140

Machine Learning: The Basics (Machine Learning: Foundations, Methodologies, and Applications)

物品 #: 52260140

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產品詳情

Shop Machine Learning: The Basics (Machine Learning: Foundations, Methodologies, and Applications) online at a best price in 香港. 9811681929
Publisher Springer
Publication date January 22, 2022
Edition 1st ed. 2022
Language English
Print length 229 pages
ISBN-10 9811681929
ISBN-13 978-9811681929
Item Weight 1.12 pounds (510 grams)
Dimensions 6.14 x 0.56 x 9.21 inches (15.6 x 1.4 x 23.4 cm)
Part of series Machine Learning: Foundations, Methodologies, and Applications

產品敘述

Machine Learning: The Basics (Machine Learning: Foundations, Methodologies, and Applications)

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客戶問題與解答

  • 題: Who is this book intended for?

    回答: This book is suitable for beginners and professionals across various fields of science and engineering.
  • 題: What key concepts does the book cover?

    回答: It covers the principles of machine learning, including data, model, loss, regularization, privacy-preservation, and explainability.
  • 題: How can this book help with ML applications?

    回答: It trains readers to break down ML applications into manageable components, helping them choose appropriate methods.

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  • A bit bulky for smaller spaces.

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現在訂購，約可在下列時間收貨： 星期二, 八月 25

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特色和優勢

  • Essential guide to understanding machine learning principles.
  • Comprehensive coverage of ML methodologies and applications.
  • Focus on data, model, and loss for effective ML implementation.
  • Equips readers with tools to select the right ML methods.
  • Ideal for both beginners and professionals in various fields.
  • Promotes understanding of key concepts like regularization and privacy-preservation.

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