Deep Learning Programs and Notes Welcome to the Deep Learning repository! This repository contains implementations, experiments, and learning materials related to various topics in Deep Learning. It is intended for students, researchers, or anyone interested in understanding and applying deep learning concepts.
📚 Contents
- Programs This section includes Python code and Jupyter notebooks covering key Deep Learning topics such as:
Neural Networks (NNs)
Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs, LSTMs)
Generative Adversarial Networks (GANs)
Autoencoders
Transformers and Attention Mechanisms
Transfer Learning
Hyperparameter Tuning
Custom Datasets and Data Augmentation
- Learning Resources Lecture notes
Concept summaries
Mathematical foundations
Paper reviews
Cheat sheets
Helpful links to blogs, articles, and courses
🛠️ Technologies Used Python 3.x
PyTorch / TensorFlow / Keras
NumPy, Pandas, Matplotlib, Seaborn
Jupyter Notebooks
Google Colab (for experiments)