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The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition

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The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition

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 Computers & Technology , Computer Science , AI & Machine Learning , Intelligence & Semantics
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“The Elements of Statistical Learning” is a comprehensive textbook offering a rigorous introduction to the field of statistical learning. This second edition builds upon the original’s foundational concepts, providing a detailed exploration of data mining, inference, and prediction techniques.

Key Highlights

  • Gain a solid understanding of core statistical learning methods.
  • Explore a wide range of algorithms for data analysis and modeling.
  • Benefit from clear explanations and numerous examples illustrating practical applications.
  • Suitable for readers with a background in mathematics and statistics.

Useful Facts

  • Publisher: Springer
  • Publication Date: February 9, 2009
  • Edition: Second Edition 2009
  • Language: English
  • Pages: 767
  • Dimensions: 9.3 x 6 x 1.4 inches

Good Fit For

  • Students and researchers in computer science, statistics, and related fields.
  • Data scientists and analysts seeking to deepen their knowledge of statistical modeling.
  • Anyone interested in learning the theoretical foundations of machine learning.
Main Specification
Brand by Trevor Hastie (Author) or Robert Tibshirani (Author) or Jerome Friedman (Author) & 0 more Format: Hardcover
Publication Date 2009 or February 9
Item Weight 3.1 pounds
Product information
Language English
Others
Product Type Intelligence & Semantics
Edition Second Edition 2009
Publisher Springer
Print length 767 pages
ISBN-10 0387848576
ISBN-13 978-0387848570
Dimensions 9.3 x 6 x 1.4 inches
ISBN10 0387848576
ISBN13 978-0387848570

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