| SNo. | Examples | Comments |
|---|---|---|
| 0 | Basic Operations | Mat Mul , Gradient Checking |
| 1 | Feed Forward MNIST | Two Layer Network |
| 2 | Linear Regression | Plotting Examples |
| 3 | Logistic Regression | MNIST Dataset |
| 4 | Simple CNN | CNN on MNIST |
| 5 | Wide Resnet | CIFAR 10, original code, arxiv |
| 6 | Tensorboard Example | Refactor Code with TFBoard |
| 7 | CIFAR 10 | With SENET Arch |
| 8 | Pre Trained Model | With MNIST |
| 9 | Predict Fast AI | Fast dot ai pytorch predict |
| 10 | DogsvsCats | Initial Code |
Resources
- Deep Learning Course
- ULaval Tutorial
- PyTorch for DL researchers
- Fast AI Coursework
- MILA PyTorch
- CS-224n
- CS-231n
- PyTorch Exercise
TODO:
- Word Embedding (http://on-demand.gputechconf.com/gtc/2017/video/s7634-jeremy-howard-build-a_neural_translation_system_from_scratch_with_pytorch.mp4)
- Style Transfer
- RNN
- Mixture Of Expert
- Model Compression
- Adversarial Generation
- Time Series
- Attention
- Document Summarization