A repository showcasing ML/DL fundamentals, paper implementations, deep learning models, and other projects. The purpose of this repository is to provide a playground for me to explore and learn about PyTorch, deep learning, and generative AI.
- PyTorch Fundamentals: A collection of PyTorch fundamentals.
- ResNet: A PyTorch implementation of ResNet (Residual Neural Network).
- RNN: A PyTorch implementation of RNN (Recurrent Neural Network).
- GAN: A PyTorch implementation of GAN (Generative Adversarial Network).
- Autoencoder: A PyTorch implementation of Autoencoder.
- Variational Autoencoder: A PyTorch implementation of Variational Autoencoder.
- Vector Quantized Generative Adversarial Network: A PyTorch implementation of VQGAN (Vector Quantized Generative Adversarial Network).
- Diffusion Models: A PyTorch implementation of Diffusion Models.