This repository contains my hands-on implementations of various Deep Learning concepts and models using Keras and PyTorch. Each folder focuses on a specific topic with notebooks, experiments, and small projects.
- Neural Network Basics: Perceptron, Gradient Descent, Backpropagation
- Model Optimization: Dropout, Batch Normalization, Early Stopping, Weight Initialization
- CNNs: Padding, Pooling, LeNet, Data Augmentation, Transfer Learning
- RNNs: Simple RNNs, LSTMs, GRUs, Bidirectional RNNs
- Projects: Brain Tumor Detection, Cats vs Dogs, DeepFake Detection, NLP tasks
- PyTorch: Autograd, DataLoader, Training Pipelines, GPU optimization, Optuna tuning
Clone the repository:
git clone https://github.com/your-username/DL_Learning.git
cd DL_LearningOpen notebooks and explore topic-wise folders.
This repository is mainly for my learning. Suggestions, improvements, and pull requests are welcome!
Happy Learning 🚀