PyTorch Deep Learning Lab
40+ experiments that build intuition for autograd, optimization, and model behavior.
PythonPyTorchNumPyMatplotlib
PyTorch Deep Learning Lab
A lab-style repo designed for learning by experiment: small, controlled setups, consistent diagnostics, and clear plots.
Architecture overview
Notebook-driven lab modules: experiment → instrumentation (hooks/plots) → interpretation. Focused on gradient flow, autograd mechanics, and minimal “magic.”
Key technical decisions
- PyTorch for transparency and easy debugging.
- Matplotlib for direct control over diagnostics/plots.
- Small, reproducible notebooks to keep concepts isolated.
Results / metrics
40+ experiments paired with 32+ long-form articles in “PyTorch Zero to One,” so readers can reproduce and extend each idea.
What I learned
How to design experiments that teach intuition (not just API usage), and how to build lightweight tooling that makes training dynamics visible.