| 000 | 00000cam u2200205 a 4500 | |
| 001 | 000045892084 | |
| 005 | 20221123181739 | |
| 008 | 170105s2016 maua b 001 0 eng d | |
| 010 | ▼a 2016022992 | |
| 020 | ▼a 9780262035613 (hardcover : alk. paper) | |
| 035 | ▼a (KERIS)REF000018128489 | |
| 040 | ▼a DLC ▼b eng ▼e rda ▼c DLC ▼d 211009 | |
| 050 | 0 0 | ▼a Q325.5 ▼b .G66 2017 |
| 082 | 0 0 | ▼a 006.3/1 ▼2 23 |
| 084 | ▼a 006.31 ▼2 DDCK | |
| 090 | ▼a 006.31 ▼b G651d | |
| 100 | 1 | ▼a Goodfellow, Ian. |
| 245 | 1 0 | ▼a Deep learning / ▼c Ian Goodfellow, Yoshua Bengio, and Aaron Courville. |
| 260 | ▼a Cambridge, MA : ▼b MIT Press, ▼c c2016. | |
| 300 | ▼a xxii, 775 p. : ▼b ill. (some col.) ; ▼c 24 cm. | |
| 490 | 1 | ▼a Adaptive computation and machine learning series |
| 504 | ▼a Includes bibliographical references and index. | |
| 650 | 0 | ▼a Machine learning. |
| 700 | 1 | ▼a Bengio, Yoshua, ▼d 1964- ▼0 AUTH(211009)147818. |
| 700 | 1 | ▼a Courville, Aaron ▼0 AUTH(211009)147819. |
| 830 | 0 | ▼a Adaptive computation and machine learning series. |
| 945 | ▼a KLPA |
Holdings Information
| No. | Location | Call Number | Accession No. | Availability | Due Date | Make a Reservation | Service |
|---|---|---|---|---|---|---|---|
| No. 1 | Location Science & Engineering Library/Sci-Info(Stacks2)/ | Call Number 006.31 G651d | Accession No. 121238616 | Availability Available | Due Date | Make a Reservation | Service |
| No. 2 | Location Science & Engineering Library/Sci-Info(Stacks2)/ | Call Number 006.31 G651d | Accession No. 121241706 | Availability Available | Due Date | Make a Reservation | Service |
| No. 3 | Location Science & Engineering Library/Sci-Info(Stacks2)/ | Call Number 006.31 G651d | Accession No. 121245251 | Availability Available | Due Date | Make a Reservation | Service |
| No. 4 | Location Science & Engineering Library/Sci-Info(Stacks2)/ | Call Number 006.31 G651d | Accession No. 121260695 | Availability Available | Due Date | Make a Reservation | Service |
Contents information
Author Introduction
요슈아 벤지오(지은이)
몬트리올 대학교의 컴퓨터 과학 교수이다.
이안 굿펠로(지은이)
구글의 연구 과학자이다.
에런 쿠빌(지은이)
몬트리올 대학교의 컴퓨터 과학 조교수이다.
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.
