Stanford's new CS 312 'Deep Learning Alchemy' course makes all materials public
stanfordnlp · x · 2026-09-14
Stanford's Fall 2026 course CS 312 'Deep Learning Alchemy', taught by Tatsunori Hashimoto and Suhas Kotha, will make all lectures and materials public.
- Core thesis: 'alchemy is learned by hand' — textbook mental models like bias-variance tradeoffs no longer hold in the scaling era, and there is no substitute for running many experiments.
- 'Prediction is understanding': students are graded on predicting held-out experiment outcomes before results come in.
- Seven units: hyperparameter tuning and scaling, hyperparameter invariances, sharp vs flat basins, scaling model capacity, stability across depth/time, generalization and data-efficient algorithms, plus applications in DNA.
- 5-unit class; enrollment is full with a waitlist open.
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