Writing Training & Evaluation Loops — Roadmap Step & Resources
The standard forward/loss/backward/step loop and tracking metrics correctly
- Level: intermediate
- Estimated time: 2 days
- Roadmap: Deep Learning & Neural Networks
Before this step
Mini projects
- Write a complete training and validation loop for an MNIST classifier from scratch
Interview questions
- Why must you call optimizer.zero_grad() before each backward pass?
Study resources
- Optimizing Model Parameters (Article) — The official PyTorch documentation's tutorial on writing a training loop.
- PyTorch Training Loop Explained (Video) — Covers writing a full train/validation loop from scratch in PyTorch.
Part of
- Deep Learning Frameworks in Depth — section
- Deep Learning & Neural Networks roadmap — the full learning path