Find your gap.

Pick a topic you want to understand. You’ll see every prerequisite traced down to the foundations it rests on. Check off what you already know. What remains is your reading list.

Your target topic

Bounds on how far random variables deviate from their expectations: Markov, Chebyshev, Hoeffding, and Bernstein. Used throughout generalization theory, bandits, and sample complexity.

Before Concentration Inequalities, you should know:

0 / 4 (0%)

3 steps back(1)

Basic Logic and Proof Techniques
layer 0A·tier 2·read →
- principle-of-mathematical-induction

Two steps back(1)

Sets, Functions, and Relations
layer 0A·tier 1·read →
- cantor-theorem

Direct prerequisites(2)

Common Probability Distributions
layer 0A·tier 1·read →
- gaussian-pdf-derivation
Expectation, Variance, Covariance, and Moments
layer 0A·tier 1·read →
- variance-of-sum
- chebyshev-inequality

How this works

BFS backward. Starting from your target, we walk the prerequisitesgraph until we hit the foundations. Each topic’s depth is its shortest distance from your target.
Must-know-cold items. The sub-checkboxes inside each topic are the specific facts and theorems you should be able to state without notes. Expand a topic to see them.
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