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.