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CS109
Lectures
Week 1
1 - Counting
Slides
Lecture Notes
2 - Permutations and Combinations
Slides
Lecture Notes
3 - Axioms of Probability
Slides
Lecture Notes
Week 2
4 - Conditional Probability and Bayes
Slides
Lecture Notes
5 - Independence
Slides
Lecture Notes
6 - Random Variables and Expectation
Slides
Lecture Notes
Week 3
7 - Variance, Bernoulli, Binomial
Slides
Lecture Notes
8 - Poisson and More
Slides
Lecture Notes
Week 4
9 - Continuous Random Variables
Slides
Lecture Notes
10 - The Normal Distribution
Slides
Lecture Notes
11 - Joint Distributions
Slides
Lecture Notes
Week 5
12 - Continuous Joint Distributions
Slides
Lecture Notes
13 - Independent Random Variables
Slides
Lecture Notes
14 - Conditional Distributions
Slides
Lecture Notes
Week 6
15 - Correlation and Covariance
Slides
Lecture Notes
16 - Great Expectations
Slides
Lecture Notes
17 - Beta
Slides
Lecture Notes
Week 7
18 - Central Limit Theorem
Slides
Lecture Notes
19 - Sampling/Bootstrapping
Slides
Lecture Notes
Week 8
20 - General Inference
Slides
Lecture Notes
21 - Parameters and MLE
Slides
Lecture Notes
22 - Gradient Ascent
Slides
Lecture Notes
Week 9
23 - Maximum A Posteriori
Slides
Lecture Notes
24 - Naive Bayes
Slides
Lecture Notes
25 - Logistic Regression
Slides
Lecture Notes
Week 10
26 - Deep Learning
Slides (Coming Soon)
Lecture Notes
27 - CS109 Review
Slides
Problem Sets
Problem Set 1
Problem Set 2
Problem Set 3
Problem Set 4
Problem Set 5
Problem Set 6
PS 1 Solution
PS 2 Solution
PS 3 Solution
PS 4 Solution
PS 5 Solution
PS 6 Solution
Midterm
Midterm Solution
Contest
Final Solution
Section
Section 1
Handout
Solutions
Concept Check
Section 2
Handout
Solutions
Notebook
Notebook Solution
Concept Check
Section 3
Handout
Solutions
Concept Check
Section 4
Handout
Solutions
Notebook
Notebook Solution
Concept Check
Section 5
Handout
Solutions
Concept Check
Section 6
Handout
Solutions
Concept Check
Section 7
Handout
Solutions
Notebook
Notebook Solution
Concept Check
Section 8
Handout
Solutions
Notebook
Notebook Solution
Concept Check
Section 9
Handout
Solutions
Section Attendance
Handouts/Demos
Administrivia
Calculation Ref
Python for Probability
Python Session Slides
Standard Normal Table
Normal CDF Calculator
Midterm Info/Practice
Final Info/Practice
Serendipity
Medical Bayes
Galton Board (Binomial)
Jurors
Federalist Papers
Dart (Joint)
Beta
Bootstrap
WebMD (Inference)
MLE and Gradient Ascent
Staff / Office Hours
Schedule
CS109 Teaching Team (and Office Hours)
Location:
Where are office hours?
Teaching Team
Instructor: David Varodayan
varodayan @ stanford
Gates 161
W 3:00-5:00pm
Head TA: Alex Tsun
alextsun @ stanford
W 3:30pm Lathrop 290
W 4:30pm Lathrop 290
TA: Oishi Banerjee
oishib @ stanford
F 3:30pm 160-323
F 4:30pm 160-323
TA: Tim Gianitsos
tgianit @ stanford
W 6:30pm 160-319
W 7:30pm 160-319
TA: Cooper Raterink
crat @ stanford
F 9:30am Lathrop 296
F 10:30am Lathrop 296
TA: Gili Rusak
gili @ stanford
W 5:30pm Lathrop 290
W 6:30pm Lathrop 290
TA: Anand Shankar
anand7 @ stanford
Th 1:30pm Encina W 101
Th 2:30pm Encina W 101
TA: Sri Somasundaram
sriramso @ stanford
Th 1:30pm Lathrop 292
Th 2:30pm Lathrop 292
TA: Emma Spellman
espell @ stanford
Th 9:30am Thornton 211
Th 10:30am Thornton 211
TA: Julie Wang
juliesw @ stanford
Th 4:30pm 200-201
Th 5:30pm 200-201