Deep learning / Ian Goodfellow, Yoshua Bengio, Aaron Courville.
By: Goodfellow, Ian [author.]
.
Contributor(s): Bengio, Yoshua [author.] | Courville, Aaron [author.].
Material type: 
TextSeries: Adaptive computation and machine learning.Publisher: Cambridge, Massachusetts : The MIT Press, [2016]Copyright date: ©2016Description: xxii, 775 pages : illustrations (some color) ; 24 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9780262035613 (hardcover : alk. paper); 0262035618 (hardcover : alk. paper).Subject(s): Machine learningDDC classification: 006.3/1 | Item type | Home library | Call number | Status | Date due | Barcode | Item holds |
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KCST Library | 006.31 Go De (Browse shelf) | Available | 1000000011 |
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| 006.3 Ha El The elements of statistical learning : | 006.3 Ru Ar Artificial intelligence : | 006.31 Ba Ba Bayesian reasoning and machine learning / | 006.31 Go De Deep learning / | 006.31 Su Re Reinforcement learning : | 006.31 Th Ma Machine learning for absolute beginners : | 006.312 On Do Doing data science : |
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.
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