1. Clone the git repo:

git clone [email protected]:zhangshuyue-neu/Demo.git

2. Run the installation command:

python setup.py develop
pip install -r requirements.txt

It is recommended to create a directory named work_dirs and put temporary results into it.

Demos for deep learning.

1. Logistic Regression
2. Shallow Nerual Network
3. Deep Nerual Network (MLP)
4. Parameter Initialization
5. Regularization
6. Advanced Optimizer (mini-batch, momentum, Adam)
7. Multiclass Classification with TensorFlow and PyTorch
8. NumPy Convolution 2D
9. Basic CNN
10. ResNet
11. NMS
12. My YOLO model
13. Letter level language model with PyTorch
14. Sentiment analysis using Glove with PyTorch
15. Date translation attention model with PyTorch
16. Transformer cn-en translation with PyTorch

1. VAE with PyTorch
2. DDPM with PyTorch
3. PixelCNN with PyTorch
4. VQVAE with PyTorch
5. DDIM with PyTorch

1. Style Transfer with PyTorch
2. PyTorch DDP Demo