Introduction to deep learning
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- 9780262039512
- 006.31 23 CHA-I
- Q325.7 .C43 2018
Contents:
1. Feed-forward neural nets 2. Tensorflow 3. Convolutional neural networks 4. Word embeddings and recurrent NNs 5. Sequence-to-sequence learning 6. Deep reinforcement learning 7. Unsupervised neural-network models.
Item type | Current library | Collection | Call number | Status | Notes | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|---|---|
![]() |
IIITD Reference | Computer Science and Engineering | CB 006.31 CHA-I (Browse shelf(Opens below)) | Available | DBT Project Grant | 012886 |
Total holds: 0
Browsing IIITD shelves, Shelving location: Reference, Collection: Computer Science and Engineering Close shelf browser (Hides shelf browser)
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
||
CB 006.301 BOS-S Superintelligence : paths, dangers, strategies | CB 006.301 TEG-L Life 3.0 : being human in the age of artificial intelligence | CB 006.31 BUD-F Fundamentals of deep learning : | CB 006.31 CHA-I Introduction to deep learning | CB 006.31 DOM-M The master algorithm : how the quest for the ultimate learning machine will remake our world | CB 006.31 EKM-L Learning deep learning : theory and practice of neural networks, computer vision, natural language processing, and transformers using tensorflow | CB 006.31 GOO-D Deep learning |
Includes bibliographical references (pages 165-168) and index.
1. Feed-forward neural nets 2. Tensorflow 3. Convolutional neural networks 4. Word embeddings and recurrent NNs 5. Sequence-to-sequence learning 6. Deep reinforcement learning 7. Unsupervised neural-network models.
There are no comments on this title.