Deep learning with PyTorch
Stevens, Eli
Deep learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann - New York : Manning, ©2020 - xxviii, 490 p. : ill. ; 24 cm.
Includes bibliographical references and index.
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.
9781617295263
Machine learning.
Neural networks
006.32 / STE-D
Deep learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann - New York : Manning, ©2020 - xxviii, 490 p. : ill. ; 24 cm.
Includes bibliographical references and index.
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.
9781617295263
Machine learning.
Neural networks
006.32 / STE-D