Goodfellow, Ian
Deep learning Ian Goodfellow, Yoshua Bengio, and Aaron Courville - Cambridge, Massachusetts : The MIT Press, c2016. - xxii, 775 p. : ill. ; 24 cm. - Adaptive computation and machine learning, 2017 : 1 . - Adaptive computation and machine learning .
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.
9780262035613
Machine learning
006.31 GO DE
Deep learning Ian Goodfellow, Yoshua Bengio, and Aaron Courville - Cambridge, Massachusetts : The MIT Press, c2016. - xxii, 775 p. : ill. ; 24 cm. - Adaptive computation and machine learning, 2017 : 1 . - Adaptive computation and machine learning .
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.
9780262035613
Machine learning
006.31 GO DE