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Deep Learning
Material type:
TextSeries: Adaptive Computation and Machine Learning seriesPublication details: MIT Press Cambridge 2016Description: xiii, 775pISBN: - 9780262035613
- Linear Algebra
- Probability and Information Theory
- Numerical Computation
- Machine Learning Basics
- Deep Feedforward Networks
- Regularization for Deep Learning
- Optimization for Training Deep Models
- Convolutional Networks
- Sequence Modeling: Recurrent and Recursive Nets
- Practical Methodology
- Linear Factor Models
- Autoencoders
- Representation Learning
- Structured Probabilistic Models for Deep Learning
- Monte Carlo Methods
- Confronting the Partition Function
- Approximate Inference
- Deep Generative Models
- 006.31 GOO/D
| Item type | Current library | Call number | Copy number | Status | Date due | Barcode | Item holds | |
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IIIT Kottayam Central Library General Stacks | 006.31 GOO/D (Browse shelf(Opens below)) | Available | 1228 | ||||
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Books
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IIIT Kottayam Central Library General Stacks | 006.31 GOO/D (Browse shelf(Opens below)) | 1 | Available | 2842 | |||
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Books
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IIIT Kottayam Central Library General Stacks | 006.31 GOO/D (Browse shelf(Opens below)) | 2 | Available | 2843 |
Total holds: 0
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| 006.31 ELG/D Deep Learning for Vision Systems | 006.31 GOO/D Deep Learning | 006.31 GOO/D Deep Learning | 006.31 GOO/D Deep Learning | 006.31 GUL/D Deep Learning with TensorFlow 2 and Keras : Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API | 006.31 KRO/D Deep Learning Illustrated :A Visual Interactive Guide to Artificial Intelligence | 006.31 LAP/D Deep Reinforcement Learning Hands-On |
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