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Goodfellow, Ian

Deep learning / Ian Goodfellow, Yoshua Bengio and Aaron Courville. - Cambridge, Massachusetts : The MIT Press, [2016], ©2016. - xxii, 775 p. : ill. (some col.) ; 24 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.

ISBN: 9780262035613 (hardcover : alk. paper) 0262035618 (hardcover : alk. paper)

LCCN: 2016022992

Subjects--Topical Terms:
Machine learning,

Subjects--Index Terms: საინფორმაციო ტექნოლოგიები კომპიუტერული ტექნოლოგიები მანქანური სწავლება მანქანური სწავლების საფუძვლები გამოყენებიტი მათემატიკა

LC Class. No.: Q325.5 / .G66 2016

Dewey Class. No.: 006.3/1

Universal Decimal Class. No.: 004