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Week 16

• Please complete the course evaluation. This class has improved a great deal, directly as a result of comments from students like yourselves. I would be grateful if you could identify what you thought worked in the course, as well as what you think might be improved for future students taking the class.
• Revised paper summaries are due this Friday (Dec. 15th) at 11:59pm. I will get comments back to project groups by Wednesday morning.
• Project 2 was due Sunday; you can submit Monday or Tuesday if needed (10% penalty per day). The key for Project 2 will be posted before the exam next Monday on MyCourses, including a sample solution.
• The final exam will be on Monday Dec. 18th from 12:30-2:30 in our regular classroom. Sample exams from previous semesters may be found under the "Resources" link. Slides for a brief review given on the last day of class are available through MyCourses as well.
• I will continue to hold office hours this week.

Week 15

• This week we will have our research paper presentations in-class. This should be interesting, as a number of papers on a variety of AI applications will be presented. The revised paper summaries are due Friday, Dec. 15th at 11:59pm.
• Project 2 is due on Sunday (11:59pm)
• Tutorial this Friday before class, GOL 2500 will be on project 2.
• The final exam will be on Monday Dec. 18th from 12:30-2:30 in our regular classroom. Sample exams from previous semesters may be found under the "Resources" link.
• For our final class on Monday next week (Wk 16), we will have a brief review and I will answer questions about the final exam.

Week 14

• EXTENSION: Project 2 is due next Sunday (Dec. 10th). Projects are completed in groups of two students - go into MyCourses and select your group (under "Groups"). Research papers will be posted on MyCourses Monday evening, and will be assigned on a first-come, first-serve basis using an online poll. I will send email to the class.
• Tutorial: there will a tutorial in GOL 2500 before class on Friday. This will cover Assignment 4, the second project, and a little bit for the research presentations next week.
• All slides from Mahshad and Wei's talks, and final slides for material on logic have been posted on MyCourses. These are the last of the lecture notes/slides for the semester.
• Grades for A3 and the midterm are now available.
• Assignment 4 is due on Friday (Dec. 1st, 11:59pm)
• Group research paper presentations will be given during classes next week. Please go into MyCourses, click on "Groups" and sign up with your team members (3 students per group) before class on Wednesday. Requirements for the research paper presentation and written summary can be found under "Content" in MyCourses.
• The final exam will be on Monday Dec. 18th from 12:30-2:30 in our regular classroom. Sample exams from previous semesters may be found under the "Resources" link.

Week 13

• Project 2 has been posted, and is due Friday, Dec. 8th (11:59pm).
• Assignment 4 will be posted Tuesday evening, and is due Friday, Dec. 1st.
• Detailed requirements and papers for group research presentations will be posted after the holidays. In short, student groups will summarize a research paper in both a presentation and a short written summary. The draft summary will receive comments, and then students will be graded on their presentation and revised summary document.
• Have a nice holiday!

Week 12

• Prof. Zanibbi away - Mahshad Madhavi and Wei Zhong gave talks on deep net applications and math-aware search this week.

Week 11

• Assignment 3 is due Monday at 11:59pm.
• Project 2 will be posted later this week.
• We will cover more on propositional logic Monday. Wednesday and Friday, Mahshad Mahdavi (a PhD student) will talk about the foundations of deep neural networks (note: some of this material may appear on the final exam).

Week 10

• Assignment 3 has been posted, and is due next Monday at 11:59pm.
• Project 2 (on machine learning) will be posted next Friday.
• Note: I am traveling for most of the next two weeks. Mahshad Madhavi will be giving some introductory lectures on deep neural networks next Wednesday and Friday, and the following Monday (Week 12). Wei Zhong will give a talk on Information Retrieval (search engines) for math formulas on Wednesday of Week 12.

Week 9

• The midterm will be given in-class on Friday. Sample midterms are available through the "Resources" link above.
• Tutorial: before the midterm on Friday, there will be a tutorial in GOL 2500.
• A key for Project 2 (including sample code) will be posted on Tuesday.

Week 8

Project 1 is due Friday at 11:59pm. Make sure to submit your materials using your group/team dropbox.
• The midterm will be given in-class next Friday. It will cover all topics discussed in-class (and in the related readings) up to the end of this week.
• Assignment 3 will be given out after the mideterm.
• There will be a tutorial this Friday, in the 'regular' room (GOL 2500).

Week 7

• Project 1 is due next Friday at 11:59pm. (Oct. 20th)
• Students who have not yet created a group in MyCourses for Project 1 need to do so ASAP. Instructions for this were sent out in an earlier email.
• There will be a tutorial this Friday. The tutorial will focus on Project 1 (Room: GOL 2590) - Note room change (this week only).
• We will continue our introduction to machine learning, talking about decision trees and AdaBoost this week.

Week 6

• There will be no class on Monday (due to the holiday).
• Office Hours: I have moved my Friday office hours after class, due to repeated conflicts with the lunch-time slot.
• Project 1 has been posted. Please create your group ASAP on MyCourses, and at the latest before class on Wednesday next week.
• Due to the Career Fair, grades for Assignment 2 will be available next week.
• There will be a tutorial this Friday. The tutorial will focus on Project 1 (Room: GOL 2500).
• We will start talking about decision trees this week.

Week 5

• There will be no tutorial this Friday. There will be a tutorial next Friday related to the project.
• The solution key for Assignment 2 has been posted on MyCourses.
• We will start talking about probability this week, in preparation for our unit on Machine Learning.

Week 4

• Assignment 2 is due Friday at 11:59pm (submitted through MyCourses).
• Tutorial: there will be a tutorial this Friday related to game search and Assignment 2.
• The solution key for Assignment 1 has been posted on MyCourses.
• We will be talking about minimax and game search this week (see assigned reading under the "Schedule" link).

Week 3

• Office hours on Friday will be from 2:30-3:30pm.
• Assignment 1 is due this Friday at 11:59pm. The assignment materials are available through MyCourses.
• Tutorials
  • Materials from the tutorial on Friday are available through MyCourses.
  • There will be a tutorial this Friday in GOL 2500, which will focus on the Assignment.
• This week we will discuss *informed* search, where we are able to use heuristics to estimate how close states are to goal states.
  • Read the pertinent sections of the course text on Informed Search (see Schedule link, above).
• Coming up: Assignment 2 will be posted late on Friday, and due next Friday.

Week 2

• Assignment 1 has been posted on MyCourses. It is due next Friday (Wk 3).
• This week we discussed Uninformed Search, where algorithms do not have a way to identify which states are closer to the goal. Make sure to also read the pertinent sections of the course text (see Schedule link above).

Week 1

• The course syllabus, course schedule, and assigned readings are available through the links above.
• Lecture slides will be available through MyCourses.
• The first tutorial will be given by the TA (Karan) next Friday at 12:20-1:15 (Room: GOL 2500). This will be a review of material related to the first assignment.
  • Note: all tutorials will be in GOL 2500, possibly with the exception of Friday Oct. 13th (which if held, will be in GOL 2590).