000			01811cam a2200265 i 4500
005			20250630165030.0
008			180514s2018 maua b 001 0 eng
020			_a9780262039406
040			_aCSL _cCSL
041			_2eng _aeng
084			_aD65,8(B):(S:72) Q8 _qCSL
100	1		_aMohri, Mehryar _eauthor. _9751616
245	1	0	_aFoundations of Machine Learning
250			_a2nd ed.
260			_aCambridge : _bThe MIT Press, _c2018.
300			_axv, 486p. _b: col. ill. _c; 24 cm.
500			_aIncludes bibliographical references and index.
520			_aThis book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition.
650		0	_aReinforcement learning. _9733538
650		0	_aKernel methods. _9814504
650		0	_aOnline learning. _9814505
700	1		_aRostamizadeh, Afshin _eco-author. _9751617
700	1		_aTalwalkar, Ameet _eco-author. _9751618
942			_2CC _n0 _cTEXL _e2nd ed. _hD65,8(B):(S:72) Q8
999			_c1432900 _d1432900