Deep Learning

This section focuses on deep learning systems that learn complex representations from data.

The projects in this folder explore neural network architectures such as ANN and CNN, with an emphasis on how deep learning models extract patterns, learn hierarchical features, and generalize to real-world inputs. The goal is not just training deep models, but understanding why they work and how to design them effectively.

This folder represents my hands-on approach to deep learning — moving beyond theory to build, evaluate, and improve models as part of complete, end-to-end systems.