000			01744cam a2200445 i 4500
999			_c112385 _d112385
003			BJBSDDR
005			20230411090108.0
007			ta
008			170612s2017 mau b 001 0 eng
020			_a9780262037310 (hardcover : alk. paper)
040			_aDLC _beng _cDLC
041			_aspa
042			_apcc
050	0	0	_aQ 325.5 _bP482e 2017
082	0	0	_a006.3/1 _223
100	1		_aPeters, Jonas, _d1984- _eauthor.
245	1	0	_aElements of causal inference : _bfoundations and learning algorithms / _cJonas Peters, Dominik Janzing, and Bernhard Schölkopf.
264		1	_aCambridge, Massachuestts : _bThe MIT Press, _c[2017]
300			_axiv, 265 pages ; _c24 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
490	0		_aAdaptive computation and machine learning series
504			_aIncludes bibliographical references (pages 235-262) and index.
520			_aA concise and self-contained introduction to causal inference, increasingly important in data science and machine learning.
650		0	_aMachine learning.
650		0	_aLogic, Symbolic and mathematical.
650		0	_aCausation.
650		0	_aInference.
650		0	_aComputer algorithms.
650		4	_aAprendizaje automático. _911390
650		0	_aCausalidad _911391
650		4	_aAlgoritmos. _92051
700	1		_aJanzing, Dominik, _eauthor. _911392
700	1		_aSchölkopf, Bernhard, _eauthor. _911393
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2lcc _cBK
946			_iLYD