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## Details

Document Type: | Book |
---|---|

All Authors / Contributors: |
Ian Goodfellow; Yoshua Bengio; Aaron Courville |

ISBN: | 9780262035613 0262035618 |

OCLC Number: | 955778308 |

Description: | xxii, 775 pages : illustrations (some color) ; 24 cm. |

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. |

Series Title: | Adaptive computation and machine learning. |

Responsibility: | Ian Goodfellow, Yoshua Bengio, and Aaron Courville. |

More information: |

### Abstract:

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.
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## Reviews

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Publisher Synopsis

[T]he AI bible... the text should be mandatory reading by all data scientists and machine learning practitioners to get a proper foothold in this rapidly growing area of next-gen technology.-Daniel D. Gutierrez, insideBIGDATA Read more...

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