000			02441nam\a2200325\a\4500
001			57710
005			20260223112331.0
008			260223s2020 nyu b 001 0 eng
020			_a9781108485067 _q(hardback)
020			_z9781108755528 _q(epub)
040			_aDLC _beng _erda _cDLC _dBD-DhIUB
082	0	0	_a004 _223 _bB6584f
100	1		_aBlum, Avrim, _d1966- _eauthor.
245	1	0	_aFoundations of data science / _cAvrim Blum, Toyota Technological Institute at Chicago, John Hopcroft, Cornell University, New York, Ravindran Kannan, Microsoft Research, India.
250			_aFirst edition.
260			_aUnited Kingdom: _bCambridge University Press, _c2020
300			_aviii,424pages _c25cm
504			_aIncludes bibliographical references and index.
520			_a"This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data"--
526			_aCSE _bps _lREF
541			_aTRIM
650		0	_aComputer science.
650		0	_aStatistics.
650		0	_aQuantitative research.
700	1		_aHopcroft, John E., _d1939- _eauthor.
700	1		_aKannan, Ravindran, _d1953- _eauthor.
776	0	8	_iOnline version: _aBlum, Avrim, 1966- _tFoundations of data science _bFirst edition. _dNew York, NY : Cambridge University Press, 2020. _z9781108755528 _w(DLC) 2019038134
942			_2ddc _cBK
999			_c57710 _d57884