Deep learning - Goodfellow, Ian; Bengio, Yoshua; Courville, Aaron (Cambridge, Massachusetts : The MIT Press, 2016)
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.
Includes bibliographical references (pages [711]-766) and index.
AAL
Development Book Agency
Keywords: Machine learning; Computer science