Deep learning : a practitioner's approach
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- 9789352136049
- 006.31 23 PAT-D
- Q325.5
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds |
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IIITD General Stacks | Computer Science and Engineering | 006.31 PAT-D (Browse shelf(Opens below)) | Checked out | 24/06/2024 | 008723 | |
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IIITD Reference | Computer Science and Engineering | REF 006.31 PAT-D (Browse shelf(Opens below)) | Available | 008722 |
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REF 006.31 MIT-M Machine learning | REF 006.31 MOH-F Foundations of machine learning | REF 006.31 MUR-M Machine learning : a probabilistic perspective | REF 006.31 PAT-D Deep learning : a practitioner's approach | REF 006.31 SCH-B Boosting : | REF 006.31 SCH-L Learning with kernels : | REF 006.31 SHA-K Kernel methods for pattern analysis |
Includes bibliographical references and index.
A review of machine learning -- Foundations of neural networks and deep learning -- Fundamentals of deep networks -- Major architecture of deep networks -- Building deep networks -- Tuning deep networks -- Tuning specific deep network architectures -- Vectorization -- Using deep learning and DL4J on Spark -- What is artificial intelligence? -- RL4J and reinforcement learning -- Numbers everyone should know -- Neural networks and backpropagation: a mathematical approach -- Using the ND4J API -- Using DataVec -- Working with DL4J from source -- Setting up DL4J projects -- Setting up GPUs for DL4J projects -- Troubleshooting DL4J installations.
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