Week 13 Part IV · Integration
Transfer learning and fine-tuning; model inference; the end-to-end workflow into the advanced courses.
Curated, free, canonical references for this week: a course or lecture, a book chapter, a video, and an authoritative blog post or official tutorial. Each opens in a new tab.
Lays out the two core strategies (fixed feature extractor vs fine-tuning) and when to use each.
A runnable PyTorch walkthrough of fine-tuning a pretrained ResNet-18, including layer-wise rates.
Trains a real image classifier end-to-end via transfer learning on a pretrained model.
Official tutorial demonstrating both fine-tuning and fixed-feature-extractor transfer learning.