Fundamentals of deep learning : designing next-generation machine intelligence algorithms
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- 9789352135608
- 006.31 23 BUD-F
- TA347.A78 B83 2017
Contents:
The neural network -- Training feed-forward neural networks -- Implementing neural networks in TensorFlow -- Beyond gradient descent -- Convolutional neural networks -- Embedding and representation learning -- Models for sequence analysis -- Memory augmented neural networks -- Deep reinforcement learning.
Item type | Current library | Collection | Call number | Status | Notes | Date due | Barcode | Item holds |
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IIITD Reference | Computer Science and Engineering | CB 006.31 BUD-F (Browse shelf(Opens below)) | Available | DBT Project Grant | 008756 | ||
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IIITD General Stacks | Computer Science and Engineering | 006.31 BUD-F (Browse shelf(Opens below)) | Available | 008720 | |||
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IIITD Reference | Computer Science and Engineering | REF 006.31 BUD-F (Browse shelf(Opens below)) | Not for loan | 008721 |
Total holds: 0
Browsing IIITD shelves, Shelving location: Reference, Collection: Computer Science and Engineering Close shelf browser (Hides shelf browser)
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REF 006.31 AFF-G Genetic algorithms and genetic programming : | REF 006.31 BAR-B Bayesian reasoning and machine learning | REF 006.31 BEK-S Scaling up machine learning | REF 006.31 BUD-F Fundamentals of deep learning : | REF 006.31 CHA-S Semi-supervised learning | REF 006.31 CHR-S An introduction to support vector machines : | REF 006.31 CLE-M Machine learning in medicine |
Includes bibliographical references and index.
The neural network -- Training feed-forward neural networks -- Implementing neural networks in TensorFlow -- Beyond gradient descent -- Convolutional neural networks -- Embedding and representation learning -- Models for sequence analysis -- Memory augmented neural networks -- Deep reinforcement learning.
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