Week |
Monday |
Wednesday |
Friday |
1 |
Read: Ch. 1.1 - 1.2
Apr 1st
1: Counting
|
Read: Ch. 1.3 - 1.6
Apr 3rd
2: Permutations and Combinations
|
Read: Ch. 2.1 - 2.5, 2.7
Apr 5th
3: Axioms of Probability
|
2 |
Read: Ch. 3.1 - 3.3
Apr 8th
4: Conditional and Bayes
|
Read: Lecture handout
Apr 10th
5: Independence
|
Due: PSet #1
Read: Ch 3.4 - 3.5
Apr 12th
6: E[X] of Random Vars
|
3 |
Read: Chapter 4.1-4.4
Apr 15th
7: Var(X) of Random Vars
|
Read: Chapter 4.5-4.6
Apr 17th
8: Poisson Distribution
|
Read: Chapter 4.7-4.10
Apr 19th
9: Continuous Distributions
|
4 |
Due: PSet #2
Read: Chapter 5.1-5.3
Apr 22nd
10: Normal Distribution
|
Read: Chapter 5.4-5.6
Apr 24th
11: Multivariable Models
|
Read: Chapter 6.1
Apr 26th
12: Continuous Multivariable
|
5 |
Read: Chapter 6.2-6.3
Apr 29th
13: Conditional Distributions
|
Due: PSet #3
Read: Chapter 6.4-6.5
May 1st
14: Multivariate Properties
|
Read: Chapter 7.1-7.2
May 3rd
15: Cov and Corr
|
6 |
Midterm: Tuesday, May 7th
Read: Chapter 7.3-7.4
May 6th
16: Great Expectations
|
Read: Chapter 7.5-7.6
May 8th
17: Beta
|
Read: Chapter 7.7
May 10th
18: Central Limit Theorem
|
7 |
Read: Chapter 8.1-8.2, 8.5
May 13th
19: Sampling
|
Due: PSet #4
Read: Chapter 8.3-8.4
May 15th
20: General Inference
|
Read: Lecture Handout
May 17th
21: Parameters and MLE
|
8 |
Read: Lecture Handout
May 20th
22: Gradient Ascent
|
Read: Lecture Handout
May 22nd
23: Maximum A Posteriori
|
Due: PSet #5
May 24th
24: Naive Bayes
|
9 |
May 27th
Memorial Day
No class
|
Read: Lecture handout
May 29st
25: Logistic Regression
|
Read: Lecture handout
May 31st
26: Deep Learning
|
10 |
No reading
June 3rd
27: CS109 Overview
|
Due: PSet #6
June 5th
28: Beyond CS109
|
Final: June 11th
June 7th
Exams
No class
|