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Foundations of machine learning

By: Contributor(s): Material type: TextTextLanguage: English Language Series: Adaptive computation and machine learningPublication details: Cambridge MIT Press 2012 2012Description: xii , 414 p. Illustration 21 cmISBN:
  • 9780262018258
Subject(s): DDC classification:
  • 006.31 MOH
Summary: Fundamental topics in machine learning are presented along with theoretical and conceptual tools for the discussion and proof of algorithms.
Item type: Lending Books
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Item type Current library Collection Call number Status Date due Barcode Item holds
Lending Books Lending Books Applied Sciences Library Lending Section Lending Collection 006.31 MOH (Browse shelf(Opens below)) Available 113563
Sheduled Reference Sheduled Reference Applied Sciences Library Reference Section Reference Collection 006.31 MOH (Browse shelf(Opens below)) Available 113564
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Foundations of Machine Learning fills the need for a general textbook that also offers theoretical details and an emphasis on proofs. Certain topics that are often treated with insufficient attention are discussed in more detail here; for example, entire chapters are devoted to regression, multi-class classification, and ranking. The first three chapters lay the theoretical foundation for what follows, but each remaining chapter is mostly self-contained. The appendix offers a concise probability review, a short introduction to convex optimization, tools for concentration bounds, and several basic properties of matrices and norms used in the book.

Fundamental topics in machine learning are presented along with theoretical and conceptual tools for the discussion and proof of algorithms.

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