Announcements and Updates
Community COVID-19 levels are medium at this time and masks are not required. However, given our group is large and we will be close together when we meet, wearing a mask is recommended. This policy is subject to change as the COVID-19 pandemic continues to evolve.
Schedule
For future lectures, this is a tentative schedule. The
exact contents are subject to change. Links to future materials
may also be broken.
Introduction
So you think you can count?
Permutations and Combinations
Pigeonhole principle and counting practice
Conditional Probability
Bayes Theorem
Bayesian Inference & Independence
Intro to Random Variables & Expectation
Section 3
(Thurs, Apr 14)
Naive Bayes Classifier
Variance
Independence of RVs
Section 4
(Thurs, Apr 21)
Discrete Random Variables
Continuous RV Basics
Uniform RVs
Expectation & Variance of Continuous RVs
Exponential and Normal RVs
Normal Distribution
Central Limit Theorem
Application: Distinct Elements
Section 7
(Thurs, May 12)
Central Limit Theorem
Joint Distributions
Tail Bounds
Markov, Chebyshev Inequalities
Chernoff Bound
Union Bound
Maximum Likelihood Estimation
Section 8
(Thurs, May 19)
Tail Bounds
Single Parameter MLE
Maximum Likelihood Estimation
continued
Section 9
(Thurs, May 26)
MLE
Markov Chains
Final exams are scheduled at 2:30-4:20 pm and 4:30-6:20 pm in CSE2 G20 rather than our regular classroom.
(Note that the time for the morning section has changed.)
This course website heavily follows the example of the website of CSE373 2019 Spring.