Deep Learning Implementations

This repository contains implementations of various deep learning models and algorithms using both NumPy and PyTorch. Below is an overview of the implementations included in this repository:

NumPy Implementations

• Multi-Layer Perceptron (MLP)
• Batch Normalization
• Convolutional Neural Network (CNN)
• Residual Layer
• Recurrent Neural Network (RNN)
• Long Short-Term Memory (LSTM)
• Gated Recurrent Unit (GRU)

PyTorch Implementations

• Vision Transformer
• Transformer
• SimCLR (Contrastive Learning)
• YOLO (including non-max suppression)
• VQ-VAE 2
• MobileNet
• EfficientNet
• CLIP

Any corrections or suggestions are encouraged.