Book I · Chapter 2
Probability and statistics
Build from moments and distributions to estimation, uncertainty, testing, and resampling.
Chapter contents
14 entries · read in order- 01 Expectation, variance, covariance, and correlation✓ Concept
- 02 Probability distributions used in ML✓ Concept
- 03 Entropy, mutual information, and information gain✓ Concept
- 04 Epistemic vs aleatoric uncertainty✓ Concept
- 05 Bayes' rule and the posterior✓ Concept
- 06 Maximum likelihood estimation✓ Concept
- 07 Bias and variance of estimators✓ Concept
- 08 Central limit theorem✓ Concept
- 09 Hypothesis testing and confidence intervals✓ Concept
- 10 Bootstrap and resampling✓ Concept
- 11 Exponential family✓ Concept
- 12 KL divergence✓ Concept
- 13 Monte Carlo and importance sampling✓ Concept
- 14 Markov chains✓ Concept