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https://github.com/divakarkumarp/30-days-pytorch
30-days PyTorch Practice from Beginning to Advance
https://github.com/divakarkumarp/30-days-pytorch
python pytorch pytorch-implementation
Last synced: about 3 hours ago
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30-days PyTorch Practice from Beginning to Advance
- Host: GitHub
- URL: https://github.com/divakarkumarp/30-days-pytorch
- Owner: divakarkumarp
- License: apache-2.0
- Created: 2024-08-25T11:09:28.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-09-18T16:55:24.000Z (8 days ago)
- Last Synced: 2024-09-26T20:03:31.819Z (about 3 hours ago)
- Topics: python, pytorch, pytorch-implementation
- Language: Jupyter Notebook
- Homepage:
- Size: 239 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 30-days-PyTorch
| S.No. | Topic | Sub-Topic | Link |
|-------|----------------------------------------|---------------------------------------------------------|------|
| | | 0. Welcome and "What is deep learning?" | |
| | | 1. Why use machine/deep learning? | |
| | | 2. The number one rule of ML | |
| | | 3. Machine learning vs deep learning | |
| | | 4. Anatomy of neural networks | |
| | | 5. Different learning paradigms | |
| | | 6. What can deep learning be used for? | |
| | | 7. What is/why PyTorch? | |
| | | 8. What are tensors? | |
| | | 9. Outline | |
| | | 10. How to (and how not to) approach this course | |
| | | 11. Important resources | |
| | | 12. Getting setup | |
| | | 13. Introduction to tensors | |
| 1 |🛠Chapter 0 – PyTorch Fundamentals | 14. Creating tensors | |
| | | 17. Tensor datatypes | |
| | | 18. Tensor attributes (information about tensors) | |
| | | 19. Manipulating tensors | |
| | | 20. Matrix multiplication | |
| | | 21. Finding the min, max, mean & sum | |
| | | 22. Reshaping, viewing and stacking | |
| | | 23. Squeezing, unsqueezing and permuting | |
| | | 24. Selecting data (indexing) | |
| | | 25. PyTorch and NumPy | |
| | | 26. Reproducibility | |
| | | 27. Accessing a GPU | |
| | | 28. Setting up device agnostic code | |