EXAMS

Midterm
Monday, February 10
7:00PM-9:00PM
Cubberley Auditorium

Final
Wednesday, March 18
3:30PM-6:30PM
Cubberley Auditorium


TEACHING TEAM

cs109 @ cs.stanford.edu

INSTRUCTOR

David Varodayan
varodayan @ stanford
Gates 161
W 3:00-5:00pm

ANNOUNCEMENTS

PSet #2 is out
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Problem Set #2 has been released! Here is a Latex template for pset 2.

Python Tutorial this Friday
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Update (1/12/20): Session slides and last quarter's recording and slides are now up!

For those of you interested in learning/reviewing Python 3, Julie will be giving a Python tutorial on Friday, January 10, 3:30-4:20pm in 420-041. We will try our best to record this session. We recommend looking at the Colab notebook beforehand. If you need help getting set up, this Piazza post should be a good starting point.

Sign up for Section!
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Update (1/13/20): Section assignments have been released. If you did not receive an email, please contact the staff mailing list. For any other section scheduling questions, please fill out the Late & Swap form ASAP. Section starts this week.

Please sign up for section by filling out this form: https://forms.gle/bZ5RhC2gq5g7NLYo9.

Once a week you are going to meet in a small group section. We are going to find the best weekly time for everyone. Section signups will close on Saturday, January 11 at 11:59pm. Preferences are not first come first serve. For more information, visit the Section Attendance page.

PSet #1 is out
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Problem Set #1 has been released! It is due next Friday, January 17 at 1:00pm. Submission will be via Gradescope with entry code MV66N5. Office hours will start tomorrow (Thursday), and the office hours calendar will have times and locations.

We have synced the class roster with Gradescope, so your Stanford email is likely to be registered already. If not, you can join the class by going to https://gradescope.com/ and clicking the button in the top right marked "Sign Up." Select "Student," then enter the entry code, your full name, email address, and 8-digit student id.

You are encouraged to write up your problem sets using LaTeX. Templates for each Problem Set are located on their respective webpage. See this intro to LaTeX, and the LaTeX code used to generate it. Though you may install LaTeX, it is often much easier to use an online LaTeX editor. A great option is: overleaf.com.

Welcome
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Welcome to CS109! We are looking forward to a fun quarter. Class starts Monday, January 6, at 1:30pm in 420-040.

We put together some handouts to help you understand where we are going to go in CS109 and how we plan to get there.

The Administrivia handout has details on course logistics. Read this to get a sense for what CS109 is going to entail.

The Course Schedule page shows you the topics that we are going to cover in CS109 and the corresponding readings. We will also post materials from lecture on the schedule page.

The Staff / Office Hours page has contact information for TAs and the office hour calendar. Office hours will start Thursday, January 9.

Once the quarter starts, you will need to sign up for a weekly 50-minute discussion section. Details on how to sign up for section will be provided during the first week of class.


Schedule

Week Monday Wednesday Friday
1

Jan 6

1: Counting

Read: Ch 1.1-1.2

Jan 8

2: Permutations and Combinations

Read: Ch 1.3-1.6
Out: PSet #1

Jan 10

3: Axioms of Probability

Read: Ch 2.1-2.5, 2.7

2

Jan 13

4: Conditional Probability and Bayes

Read: Ch 3.1-3.3

Jan 15

5: Independence

Read: Ch 3.4-3.5

Jan 17

6: Random Variables and Expectation

Read: Ch 4.1-4.4
Due: PSet #1
Out: PSet #2

3

Jan 20

Martin Luther King Jr. Day
No Class

Jan 22

7: Variance, Bernoulli, Binomial

Read: Ch 4.5-4.6

Jan 24

8: Poisson and More

Read: Ch 4.7-4.10

4

Jan 27

9: Continuous Random Variables

Read: Ch 5.1-5.3, 5.5
Due: PSet #2
Out: PSet #3

Jan 29

10: The Normal Distribution

Read: Ch 5.4

Jan 31

11: Joint Distributions

Read: Ch 6.1

5

Feb 3

12: Continuous Joint Distributions

Read: Ch 6.1

Feb 5

13: Independent Random Variables

Read: Ch 6.2-6.3
Due: PSet #3
Out: PSet #4

Feb 7

14: Conditional Distributions

Read: Ch 6.4-6.5

6

Feb 10

15: Correlation and Covariance

Read: Ch 7.3-7.4
Midterm: Mon Feb 10, 7:00-9:00pm

Feb 12

16: Great Expectations

Read: Ch 7.1-7.2

Feb 14

17: Beta

Read: Ch 5.6.1-5.6.4, 7.5-7.6

7

Feb 17

Presidents Day
No Class

Feb 19

18: Central Limit Theorem

Read: Ch 8.3
Due: PSet #4
Out: PSet #5

Feb 21

19: Sampling/Bootstrapping

Read: Lecture Notes

8

Feb 24

20: General Inference

Read: Lecture Notes

Feb 26

21: Parameters and MLE

Read: Lecture Notes

Feb 28

22: Gradient Ascent

Read: Lecture Notes
Due: PSet #5
Out: PSet #6

9

Mar 2

23: Maximum A Posteriori

Read: Lecture Notes

Mar 4

24: Naive Bayes

Read: Lecture Notes

Mar 6

25: Logistic Regression

Read: Lecture Notes

10

Mar 9

26: Deep Learning

Read: Lecture Notes

Mar 11

27: CS109 Review

Read: Everything :)
Due: PSet #6

Mar 13

28: Beyond CS109

Last day to submit assignments
Final: Wed Mar 18, 3:30-6:30pm