Bibliograph

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

Type

Label

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

Language

eng

Bibliography note

Includes bibliographical references (pages 711-766) and index

Illustrations

illustrations

Index

index present

Literary Form

non fiction

Main title

Deep learning

Nature of contents

bibliography

Responsibility statement

Ian Goodfellow, Yoshua Bengio, and Aaron Courville

Series statement

Adaptive computation and machine learning

Table Of 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

Classification