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Goodfellow, Ian

Deep learning Ian Goodfellow, Yoshua Bengio, and Aaron Courville. - Cambridge, Mass. : MIT Press, ©2016. - xxii, 775 p. : ill. ; 25 cm. - Adaptive computation and machine learning .

Includes bibliographical references (pages 711-766) and index.

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

2016022992


Machine learning,

Q325.5 / .G66 2016

006.31 / GOO-D

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