000			01473nam a22002417a 4500
999			_c52082 _d53629
003			ISURa
008			191126b xxu||||| |||| 00| 0 eng d
020			_a9780262018258
041			_aEnglish
082			_a006.31 _bMOH
100			_aMohri, Mehryar _974282
245			_aFoundations of machine learning
260			_aCambridge _bMIT Press _c2012 _g2012
300			_axii , 414 p. _bill. _c21 cm.
440			_aAdaptive computation and machine learning. _969132
500			_aFoundations 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.
520			_aFundamental topics in machine learning are presented along with theoretical and conceptual tools for the discussion and proof of algorithms.
650			_aMachine Learning _969133
650			_aComputer Algorithms _95760
700			_aRostamizadeh, Afshin _974283
700			_aTalwalkar, Ameet _974284
942			_2ddc _cLN