Resources

A small reference shelf — use the deck first

Do not try to read everything below. The lecture decks tell you what matters in a given week; these resources are dependable places to go deeper when you need another explanation, a derivation, or implementation context.

Core references

Use this for Resource
One broad, modern textbook Simon J. D. Prince, Understanding Deep Learning
A rigorous second treatment Christopher Bishop & Hugh Bishop, Deep Learning: Foundations and Concepts
Hands-on PyTorch Dive into Deep Learning
Classical reference Goodfellow, Bengio & Courville, Deep Learning

Video companions

  • Build from scratch: Andrej Karpathy’s Zero to Hero is ideal for the early implementation thread and language-model construction.
  • Vision: CS231n is the most useful companion for CNNs, detection, and segmentation.
  • Language and Transformers: CS224N provides a deeper treatment of sequence models and attention.
  • Practical model work: the Hugging Face course is the best bridge to modern tooling.

Papers: read selectively

Read the original paper only after you understand the deck’s mechanism. The recurring landmarks are: ResNet, Attention Is All You Need, BERT/GPT, SimCLR/MAE/BYOL, VAE/GAN/DDPM, and FlashAttention. Individual deck endings name the relevant paper when it earns a close read.

Interactives

Interactive Articles hosts optional browser explainers for mechanics such as convolution, optimization, attention, contrastive learning, and diffusion. Follow the links on [I] lecture slides; they are the curated entry points rather than a separate parallel syllabus.

The course site also hosts small lecture-matched tools. The Lecture 5 EWMA + momentum explorer uses the same seeded temperature observations and computed ravine as the deck and notebook. The learning-rate schedule explorer reuses Example A and its seed-12 sampled stream to separate early travel from late settling.

For each lecture

  1. Read the deck’s opening and its worked mechanism.
  2. Use one notebook or interactive only if it resolves a concrete question.
  3. Return to the relevant book or paper afterward, with the structure already in mind.