Deep Learning for Coders with fastai and PyTorch – Jeremy Howard, SylvainGugger – 1st Edition

Preface
Foreword
I Deep learning in practice
1. Your deep learning joumey
2. Form model to production
3. Data ethics

II. Understanding fastai´s Applications
4. Under the hood: training a digit classifier
5. Image classification
6. Other computer vision Problems
7. Training a state of the art model
8. Collaborative Filtering Deep Dive
9. Tabular modeling deep dive
10. NPL deep dive RNNs
11. Data munging with fastai´s Mid Level Api

III. Foundations of deep learning
12. A language model from scratch
13. Convolutional neural networks
14. Resnets
15. Application architectures deep dive
16. The training Process

IV Deep learning from scracth
17. A neural net from the foundations
18. CNN Interpretation with CAM
19. A fastai Learner from scratch
20. Concluding Thoughts
A. Creating a blog
B. Data project checklist
Index