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Deep learning/ Ian Goodfellow, Yoshua Bengio and Aaron Courville

By: Goodfellow, IanContributor(s): Bengio, Yoshua | Courville, AaronSeries: (Adaptive computation and machine learning)Publication details: Cambridge: The MIT Press, ©2016Description: xxii, 775 p. : ill. ; 24 cmISBN: 9780262035613; 0262035618Subject(s): Machine learningDDC classification: 006.31

Contents:

Introduction -- 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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Holdings
Item type	Current library	Call number	Status	Date due	Barcode	Item holds
General Books	Central Library, Sikkim University General Book Section	006.31 GOO/D (Browse shelf(Opens below))	Available		48062

Total holds: 0

Introduction --
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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