🧠 Deep Learning Mini Projects using PyTorch.
These are mini applications of various Deep Learning algorithms in PyTorch. Most of the projects are re-implementations of some of my favorite assignments from Coursera's Deep Learning Specialization. All projects are standalone Jupyter Notebooks that can be executed independently.
- Python 3.8+
- Install dependencies:
pip install -r requirements.txt
- Feed Forward
- Cat vs Non-cat Classification
- Convolutional
- Hand Sign Recognition Using CNN
- Hand Sign Recognition Using ResNet
- Art Generation Using Neural Style Transfer
- Sequence
- Dinosaur Name Generation Using RNN
- Jazz Improvisation Using LSTM
- Emojifier Using LSTM and Word Embeddings
- Date Translation Using Neural Machine Translation
- Generative
- Wardrobe Generation Using DCGAN
- Wardrobe Generation Using VAE
If any of the high-level descriptions or comments about the algorithms and techniques inside the notebooks is wrong, or if you encounter any problems running the projects; let me know!