Probability
Uncertainty & inference — how models express and reason about what they don't know.
basic rules
Bayes' theorem
distributions
MLE & MAP
Topic overview
Use probability to reason about uncertainty: events, conditional probability, Bayes' theorem, distributions, likelihood, and posterior beliefs.
Core concepts
Understand joint, marginal, and conditional probability; independence; Bayes' theorem; common distributions; expectation; variance; MLE; and MAP.
Why it matters
Probability is the foundation for classification confidence, uncertainty estimates, generative models, Bayesian reasoning, and evaluating risk.
Interview relevance
Probability questions reveal whether you can reason from first principles under uncertainty instead of only applying formulas.