Introduction to basic concepts in probability theory. Pre-requisite to many upper-year machine learning courses.
We used the Probability, Statistics, and Random Processes for Electrical Engineering textbook, by Alberto Leon-Garcia.
Concepts covered
- Basic probability theory
- Mutual exclusivity
- Events
- Basic set operations (, , ) and De Morgan’s laws
- Finite and infinite sets (sample spaces)
- Conditional probability
- Tree diagrams
- Bayes’ theorem
- Classification metrics (accuracy)
- Combinatorics
- Rule of products, rule of sums
- Sampling {with, without} replacement, {with, without} ordering
- Permutations
- Combinations