000			a
999			_c198806 _d198806
020			_a9780262035613
020			_a0262035618
040			_cCUS
082			_a006.31 _bGOO/D
100			_aGoodfellow, Ian
245			_aDeep learning/ _cIan Goodfellow, Yoshua Bengio and Aaron Courville
260			_aCambridge: _bThe MIT Press, _c©2016.
300			_axxii, 775 p. : _bill. ; _c24 cm.
440			_a(Adaptive computation and machine learning)
505			_aIntroduction -- Applied 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			_aMachine learning
700			_aBengio, Yoshua
700			_aCourville, Aaron
942			_cWB16