Run a focused checkpoint.
Answer what you know, skip what you do not, and let the run turn weak signals into a short review path.
Scope
Run at a glance
Starts with lower-friction anchors, then checks the concentration-to-learning-theory bridge.
Focused checkpoint
Ready for the checkpoint run?
Answer what you know and skip what you do not. Misses adjust the remaining order, and the result becomes a short review path for this checkpoint.
Learning theory foundations
A curated 10-question diagnostic spine for supervised learning, overfitting, bias-variance, generalization gaps, VC dimension, ERM, Sauer-Shelah, and uniform convergence.
Learner can move from supervised-learning vocabulary to VC examples, ERM generalization, uniform convergence, Sauer-Shelah growth control, and the fundamental theorem framing.
How this run adapts
Review focus
- generalization gap
- capacity control
- ERM versus uniform convergence
- finite-class and VC prerequisites
Could unlock
- Finite Class Generalization Diagnostic
- Vc Capacity Map
Optional self-check
Leave blank if you want the neutral ramp. Pick only the areas where you have a strong signal.
Vectors, matrices, derivatives, notation.
Distributions, estimators, likelihood, concentration.
Gradients, convexity, SGD, Adam, proximal ideas.
ERM, VC, PAC, Rademacher, generalization.
Deep nets, attention, transformers, value functions.
Moving ideas across topics and checking assumptions.
This focused run uses the gold questions attached to the checkpoint. Sign in to attach it to your profile.
Browser-only run
This diagnostic will save for this browser, but it will not create account-level learning events. Sign in first if you want the run to count toward your profile.