Foundations of machine learning
Material type: TextLanguage: English Language Series: Adaptive computation and machine learningPublication details: Cambridge MIT Press 2012 2012Description: xii , 414 p. Illustration 21 cmISBN:- 9780262018258
- 006.31 MOH
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds |
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Lending Books | Applied Sciences Library Lending Section | Lending Collection | 006.31 MOH (Browse shelf(Opens below)) | Available | 113563 | ||
Sheduled Reference | Applied Sciences Library Reference Section | Reference Collection | 006.31 MOH (Browse shelf(Opens below)) | Available | 113564 |
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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