Deep learning / Ian Goodfellow, Yoshua Bengio, and Aaron Courville.

By: Goodfellow, IanContributor(s): Bengio, Yoshua | Courville, AaronMaterial type: TextTextLanguage: English Series: Adaptive computation and machine learningPublisher: United States : The MIT Press, 2016Edition: 2ndDescription: xxii, 775 pagesISBN: 9780262035613 (hardcover : alk. paper); 0262035618 (hardcover : alk. paper)Subject(s): Machine learningDDC classification: 006.3
Contents:
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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006.3 GOO/D (Browse shelf) Checked out to Abhay Jain (715ee1137) 30/11/2020 79361

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.

Comment by BILLA NIKHIL REDDY
20/02/2020

One of the best book for DL . Pls provide some more copies. My hold is in pending from 2 months.

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