This repository is a structured collection of Deep Learning concepts and implementations, designed to help beginners and intermediate learners understand and apply core neural network architectures through hands-on examples.
The repo covers Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Natural Language Processing (NLP) with clear, practical workflows.
- Fundamentals of Deep Learning
- How neural networks work internally
- Building, training, and evaluating deep learning models
- Working with structured data, images, sequences, and text
- Hands-on implementation using popular frameworks