Track 1 · Path · 8 explainers
Probability & Statistics
Distributions, Bayes, estimation, and information theory end to end
- 1
Probability & Distributions
Spam, densities, and the math of uncertainty
- 2
Statistics Essentials
Mean, variance, standard deviation, and the Central Limit Theorem
- 3
Bayes' Theorem
Updating beliefs with evidence
- 4
Hypothesis Testing
Make principled decisions from data using null hypotheses, p-values, and significance levels
- 5
Sampling & Monte Carlo
Random sampling, the law of large numbers, and Monte Carlo estimation
- 6
MLE & MAP Estimation
Maximum likelihood and maximum a posteriori — why training works
- 7
Entropy & Cross-Entropy
Measuring surprise, uncertainty, and prediction quality
- 8
KL Divergence
Measuring how different two distributions are