000			01505cam a2200229 i 4500
999			_c31807 _d31807
001			nam a22 7a 4500
020			_a9780262035613
082			_a006.31 GO DE
100	1		_aGoodfellow, Ian _96792
245	1	0	_aDeep learning _cIan Goodfellow, Yoshua Bengio, and Aaron Courville
260			_aCambridge, Massachusetts : _bThe MIT Press, _cc2016.
300			_axxii, 775 p. : _bill. ; _c24 cm.
490	1		_aAdaptive computation and machine learning, 2017 : _v1
504			_aIncludes bibliographical references (pages 711-766) and index.
505	0		_aApplied math and machine learning basics. Linear algebra -- Probability and information theory -- Numerical computation -- Machine learning basics -- Deep networks: modern practices. Deep feedforward networks -- Regularization for deep learning -- Optimization for training deep models -- Convolutional networks -- Sequence modeling: recurrent and recursive nets -- Practical methodology -- Applications -- Deep learning research. Linear factor models -- Autoencoders -- Representation learning -- Structured probabilistic models for deep learning -- Monte Carlo methods -- Confronting the partition function -- Approximate inference -- Deep generative models.
650		0	_aMachine learning _95121
700	1		_aBengio, Yoshua _96793
700	1		_aCourville, Aaron _96794
830		0	_aAdaptive computation and machine learning _96795
856			_uhttps://uowd.box.com/s/5tfcyofz1iagzl63whqgic1sfxmdzuij _zLocation Map
942			_2ddc _cREGULAR