Deep learning with PyTorch
Deep Learning with PyTorch teaches you to create neural networks and deep learning systems with PyTorch. This practical book quickly gets you to work building a real-world example from scratch: a tumor image classifier. Along the way, it covers best practices for the entire DL pipeline, including th...
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| Hlavní autoři: | , , |
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| Médium: | Livre papier |
| Jazyk: | Anglais |
| Vydáno: |
Shelter Island (N.Y.) :
Manning Publications Co
C 2020.
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| Témata: | |
| Autres localisations: | Voir dans le Sudoc |
Obsah:
- Part 1. Core PyTorch. 1. Introducing deep learning and the PyTorch library
- 2. Pretrained networks
- 3. It starts with a tensor
- 4. Real-world data representation using tensors
- 5. The mechanics of learning
- 6. Using a neural network to fit the data
- 7. Telling birds from airplanes: learning from images
- 8. Using convolutions to generalize
- Part 2. Learning from images in the real world: early detection of lung cancer. 9. Using PyTorch to fight cancer
- 10. Combining data sources into a unified dataset
- 11. Training a classification model to detect suspected tumors
- 12. Improving training with metrics and augmentation
- 13. Using segmentation to find suspected nodules
- 14. End-to-end nodule analysis, and where to go next
- Part 3. Deployment. 15. Deploying to production