A complete learning repository for Deep Learning using PyTorch, covering everything from tensors and neural networks to training pipelines and real-world projects.
This repository is built as a learning + portfolio project — every notebook here represents a concept I have learned and implemented from scratch.
Deep Learning is not about just using libraries — it is about understanding:
- How neural networks work
- How gradients flow
- How loss functions & optimizers train models
- How real training pipelines are built
This repository documents that journey in a structured, practical way.
- Python
- PyTorch
- Jupyter Notebook
- NumPy
- Matplotlib
(Updated as I learn more)
- PyTorch Tensors & Operations
- Automatic Differentiation (Autograd)
(This structure grows as new topics and projects are added.)
git clone https://github.com/KavinKohli/Deep-Learning-PyTorch.git
cd Deep-Learning-PyTorch