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Course Information
Instructor: Chris Piech
Course assistants:
Contact: Please use Piazza for all questions related to lectures, homeworks, and projects. For private questions, email: cs221-sum1213-staff@lists.stanford.edu.
Office Hours: See the office hour calendar. Additional office hours are also availible by appointment.
Book: Russell and Norvig. Artificial Intelligence: A Modern Approach, 3rd. edition.
Lectures: If you can make it to lecture come! You learn a lot from your peers and stay on track. The lectures are recorded -- so if you can't make it, or if you want to see old lectures, you can find them at myvideosu.
Prerequisites: a good grasp of basic data structures and algorithms, probability, linear algebra; solid programming skills.
Grading Policy
| Homework | 20% |
| Midterm | 20% |
| Programs | 30% |
| Final Project | 30% |
Tentative Schedule
| Date | Topic | Reading | Lecture notes | Assignment | |
|---|---|---|---|---|---|
|
[Search] |
|||||
| June 25 [Tu] | Basic Search | 1.1, 3.1 - 3.4 | slides | Pacman (due July 8th)
Search Pset [soln] (due July 8th) |
|
| June 27 [Th] | Heuristics and Chance | 3.5, 3.6, 16.1, MDPs | slides [code] | ||
| July 2 [Tu] | Adversaries | 5.1 - 5.5 | slides [code] | ||
| July 4 [Th] | No Class | None | None | ||
|
[Variable Based Models] |
|||||
| July 9 [Tu] | Variable Based Models | 6.1 - 6.5, 13.1 - 13.5 | slides |
Driverless Car (due July 22nd)
Variable Pset [soln] (due July 22nd) |
|
| July 11 [Th] | Probabilistic Models | 14.1 - 14.4 | slides | ||
| July 16 [Tu] | Temporal Models | 15.1 - 15.5 | slides | ||
| July 18 [Th] | Parameter Learning | 14.5, 20.3 | slides [code] | ||
| July 23 [Tu] | Midterm Review | Practice Midterms | slides | ||
| July 24 [We] | Midterm | Midterm Solutions | None | ||
|
[Machine Learning] |
|||||
| July 25 [Th] | Supervised Learning | 18.1-18.2, 18.6, 18.8 | slides | Visual Cortex (due Aug 5th)
Learning Pset (due Aug 5th) |
|
| July 30 [Tu] | Unsupervised Learning | 21.1-21.6, K Means | slides | Final Project (due Aug 8th, 18th) | |
| Aug 1 [Th] | Loss Minimization | None | slides | ||
| Aug 6 [Tu] | Features | Sparse Autoencoder | slides | ||
| Aug 8 [Th] | Deep Learning | None | slides | ||
|
[Applications] |
|||||
| Aug 13 [Tu] | The Big Picture | 27.1 - 27.4, Big Picture | slides | ||
| Aug 15 [Th] | Peter Norvig Guest Lecture | None | code | ||
Policies
Group Work
You are encouraged to talk about the homework assignments in small groups. However your final submission must be written up in your own words and you must not share actual lines of code with other students.
Late Policy
You have three six "late" days for the entire quarter. You can use each late day to grant yourself a 24 hour extension.
Late days either apply to an entire problem set (even though you submit each part seperately) or a programming assignment. You can use up to three
late days on an assignment. After you have used up all of your late days we will no longer accept late submissions. If an unforseen circumstance comes up
and you need an extension beyond your late days, contact Chris.
Submission
Homework assignments will have specific submission instructions included with the handouts. We will use a certain amount of automatic grading to help us deal with the massive amounts of code everyone submits, so please follow the submission instructions exactly as written!
Honor Code
You are free to discuss the assignment and solutions with others. However, you must write your own assignment, and must not represent any portion of others' work as your own. Anybody violating the honor code will be referred to the Judical-Affairs Office. If convicted, the normal penalty is a quarter suspension or worse.