Deep learning : a practitioner's approach / by Josh Patterson and Adam Gibson.
Material type: TextLanguage: English Publication details: Mumbai : O'Reilly, SPD Pvt. Ltd., 2017.Description: xxi, 507 p. : ill. ; 24 cmISBN:- 9781491914250
- 006.31 PAT/D
Item type | Current library | Home library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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Text Book | Central Library, IIT Bhubaneswar | Central Library, IIT Bhubaneswar | SES | Checked out | 02/07/2024 | TB11225 | |||
Text Book | Central Library, IIT Bhubaneswar | Central Library, IIT Bhubaneswar | SES | Checked out | 24/09/2024 | TB11224 | |||
Text Book | Central Library, IIT Bhubaneswar | Central Library, IIT Bhubaneswar | SES | Checked out | 14/10/2024 | TB11223 | |||
Course Reserve | Central Library, IIT Bhubaneswar | Central Library, IIT Bhubaneswar | SES | 006.31 PAT/D (Browse shelf(Opens below)) | Not for loan | TB11221 | |||
Text Book | Central Library, IIT Bhubaneswar | Central Library, IIT Bhubaneswar | SES | Checked out | 10/11/2024 | TB11222 |
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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.
How can machine learning--especially deep neural networks--make a real difference in your organization? This hands-on guide not only provides practical information, but helps you get started building efficient deep learning networks. The authors provide the fundamentals of deep learning--tuning, parallelization, vectorization, and building pipelines--that are valid for any library before introducing the open source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you'll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J.--
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