000			01965cam a22004098i 4500
001			22395669
003			CSPC
005			20260720140808.0
008			220125s2023 nyu 000 0 eng
010			_a 2021058431
020			_a9781266108334 _q(papercover)
035			_a22395669
040			_aDLC _beng _erda _cDLC _dCSPC
042			_apcc
050	0	0	_aHD30.23 _b.T3245 2023
082	0	0	_a658.403 _bT12m _223/eng/20220125
100	1		_aTaddy, Matt, _eauthor.
245	1	0	_aModern business analytics : _bpractical data science for decision-making / _cMatt Taddy, Leslie Hendrix, and Matthew Harding.
263			_a2202
264		1	_aNew York, NY : _bMcGraw Hill LLC, _c2023.
300			_axxii, 442 pages ; _c25 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
500			_aIncludes index.
505	0		_aRegression -- Uncertainty quantification -- Regularization and selection -- Classification -- Causal inference with experiments -- Casual inference with controls -- Trees and forests -- Factor models -- Text as data -- Deep learning.
520			_a"The practice of data analytics is changing and modernizing. Innovations in computation and machine learning are creating new opportunities for the data analyst: exposing previously unexplored data to scientific analysis, scaling tasks through automation, and allowing deeper and more accurate modeling"-- _cProvided by publisher.
521			_aAges 18+ _bMcGraw Hill Education.
650		0	_aDecision making _xEconometric models.
650		0	_aMachine learning.
700	1		_aHendrix, Leslie, _eauthor.
700	1		_aHarding, Matthew C., _eauthor.
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK _e23 _h658.403 _iT12m _kCIR _m2023 _n0
999			_c32679 _d32679