Description

This introductory course on machine learning will give an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, and Bayesian networks. The course will give the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and when they work. The underlying theme in the course is statistical inference as it provides the foundation for most of the methods covered.

General Information

Prerequisites
(6.041 or 18.05) and 18.06; 6.034 is helpful
Lectures
Tue. and Thu. 9:30AM - 11AM in 54-100
Staff mailing list
6867-staff-2012@lists.csail.mit.edu
Instructor in charge
Leslie Pack Kaelbling
Recitations
They will be on Fridays, at 12, 1, 2, and 3. They are optional and you can attend any session(s) you want to. There will be two types of recitations; see Syllabus for details. You may ignore the recitation time that you have been assigned by the registrar.
Office hours: 34-501
Monday 4PM - 6PM
Wednesday 6PM - 10PM

Announcements

Exam Tuesday Dec 4 at **9AM** in 54-100.
12/03/12 4:01 PM
Reminder! The exam was rescheduled to Tuesday December 4 because of the power outage. It will begin at 9AM in 54-100.

Don't be late. This is half an hour earlier than lecture normally starts. Don't be late.

#exam2
Project discussions, Friday Nov 2
10/29/12 9:42 AM
Here is the plan for project discussions:
- You hand in the proposals by tomorrow night (we'll keep this deadline unless the power goes out)
- We will have project discussions on Friday Nov 2, instead of recitations
- We (the staff) will divide the proposals into groups and post doodle polls on Oct 31 so each group can sign up for a meeting time
- The purpose of the discussion is for us to give you feedback on your proposals, particularly about the scope


#project
Submitting homework on Easy Chair with pairs
10/02/12 11:45 AM
If two people are working together on the homework assignment, please make sure that both of you are listed as authors on the submission. More specifically, when you click on "New Submission", you must enter information for each person working on the assignment in the Authors section. This will include the (*) information for both Author 1 and Author 2. It is a good idea to check the "Corresponding author" box for both of you as well. If this information is not entered correctly, credit for the homework will not be given correctly and reviews cannot be distributed correctly. If you have other questions, let us know.
#homework1 #homework #hw1
Recitation room change
9/06/12 4:16 PM
Our room assignments were changed for recitations. Here is the new schedule:

12:00 Room 6-120 R1
1:00 Room 6-120 R2
1:00 Rom 3-442 R1 Note: this is a smaller room
2:00 Room 3-442 R2 Note: this is a smaller room
2:00 Room 34-101 R1
3:00 Room 34-101 R2

As it says in the syllabus, R1 sessions will focus on easier examples related to the current week's work, and R2 sessions will focus on harder exercises from the previous week. This week, R2 will just be a somewhat more difficult set of problems than R2, related to background and today's lecture.


You may attend as many recitation sessions of any kind as you wish. But, unfortunately, our large room was taken back by the schedules office, so room 3-442 is smaller than the others. If you have a choice between recitation times that fit into your schedule, I would ask that you avoid the ones in 3-442. But, if that's the only way things work out for you, don't hesitate to go. It holds 50 students.
#recitations
Staff Office Hours
NameOffice Hours
Tomas Lozano-Perez
When?
Where?
Chris Amato
When?
Where?
Leslie Kaelbling
When?
Where?
Simon LUI
When?
Where?

Homework

Homework
Due Date
11/15/2012
11/15/2012
10/30/2012
10/25/2012
10/25/2012
10/03/2012
10/03/2012

Lecture Notes

Lecture Notes
Lecture Date