Syllabus

Policy
Breakdown
Grading      Grading will be based on weekly quizzes (24%), homeworks (50%) and a course project (25%). Note that 1% of your grade is assigned to Attendance.
Quizzes
Quizzes      There will be weekly quizzes.
  • We will retain your best 12 out of the remaining 14 quizzes.
  • Quizzes will generally (but not always) be released on Friday and due 48 hours later.
  • Quizzes are scored by the number of correct answers.
  • Quizzes will be worth 24% of your overall score.
Assignments
Assignments There will be four assignments in all, plus the Peer Review assignment during the last week of the semester. Assignments will include Autolab components, where you implement low-level operations, and a Kaggle component, where you compete with your colleagues over relevant DL tasks.
  • Autolab components are scored according to the number of correctly completed parts.
  • We will post performance cutoffs for HIGH (90%), MEDIUM (70%), LOW (50%), and VERY LOW (30%) for Kaggle competitions.
    Scores will be interpolated linearly between these cutoffs.
  • Each assignment will have a “early submission deadline”, an “on-time submission deadline” and a “late-submission deadline.”
    • Early submission deadline: You are required to make at least one submission to Kaggle by this deadline. People who miss this deadline will automatically lose 10% of subsequent marks they may get on the homework. This is intended to encourage students to begin working on their assignments early.
    • On-time deadline: People who submit by this deadline are eligible for up to five bonus points. These points will be computed by interpolation between the A cutoff and the highest performance obtained for the HW. The highest performance will get 105.
    • Late deadline: People who submit after the on-time deadline can still submit until the late deadline. There is a 10% penalty applied to your final score, for submitting late.
    • Slack days: Everyone gets up to 10 slack days, which they can distribute across all their homework P2s only. Once you use up your slack days you will fall into the late-submission category by default. Slack days are accumulated over all parts of all homeworks.
    • Kaggle scoring: We will use max(max(on-time score), max(slack-day score), 0.9*max(late-submission score)) as your final score for the HW. If this happens to be a slack-days submission, slack days corresponding to the selected submission will be counted.
  • Assignments carry 50% of your total score, with each of the four HWs being worth 12.5%.
  • A guided project will be released later in the course and will have the same weight as a course project. Please see Project section below for more details.
  • There are bonus assignments for each HW. Bonus points (5% total) contribute to the final score by adding on top of the base score. Notice that bonus scores for 11485 and 11685/785 are different. 11485 Base Score = Assignments (50%) + Quiz (24%) + Attendance (1%) = 75% and 11685/785 Base Score = 11485 Base Score (75%) + Project (25%) = 100%.
  • The Peer Review assignment is required of all students, 11-485/685/785. The task is for all students to review and grade 4-6 of the videos. It is to be completed over the last weekend, after classes finish (but before finals week). We will tell you which projects you have been assigned to review; each review should take around 15~20 minutes. Here is what we expect you to do for each review:
  • Watch the video carefully. As you watch the video, jot down some notes/concerns/questions that you might have.
  • Reference the initial report to clear up any confusion.
  • You must post at least one comment to the corresponding Piazza post of your reviewee. This comment must be a meaningful question or concern that demonstrates you have understood the material.
  • Finally, fill out the project review form carefully. More details will be shared over Piazza.
Project
Project
  • All students taking a graduate version of the course are required to do a course project. The project is worth 25% of your grade. These points are distributed as follows: 20% - Midterm Report; 35% - Project Video; 5% - Responding to comments on Piazza; 40% - Project report.
  • Note that a Project is mandatory for 11-785 students. In the event of a catastrophe (remember Spring 2020), the Project may be substituted with the guided project. 11-685 Students may choose to do a Project instead of the guided project. Either your Project OR the guided project will be graded.
  • Important information for project reports and video presentations (midterm report rubric, final report rubric, video timeline, and video grading): link.
Attendance
Attendance
  • If you are in section A you are expected to attend in-person lectures. We will track attendance.
  • If you are in any of the other (out-of-timezone) sections, you must watch lectures live on zoom. Real-time viewing is mandatory unless you are in inconvenient time zones. Others are required to obtain specific permission to watch the pre-recorded lectures (on MediaServices). If viewed on MediaServices, the lectures of each week must be viewed before Monday 8AM EST of the following week (otherwise, it doesn’t count).
  • At the end of the semester, we will select a random subset of lectures and tabulate attendance. If you have attended at least 70% of these (randomly chosen) lectures, you get the attendance point.
Final grade
Final grade The end-of-term grade is curved. Your overall grade will depend on your performance relative to your classmates.
Pass/Fail
Pass/Fail Students registered for pass/fail must complete all quizzes, HWs and if they are in the graduate course, the project. A grade equivalent to B- is required to pass the course.
Auditing
Auditing Auditors are not required to complete the course project, but must complete all quizzes and homeworks. We encourage doing a course project regardless.
End Policy

Study groups

We believe that effective collaboration can greatly enhance student learning. Thus, this course employs study groups for both quizzes and homework ablations. It is highly recommended that you join a study group. Check Piazza for more information.

Piazza

Piazza is what we use for discussions. You should be automatically signed up if you are enrolled at the start of the semester. If not, please sign up manually.

AutoLab

AutoLab is where all the homework assignments are posted. You will also use Autolab to submit your solutions and test your implementations based on the scores given by the autograder. You can make multiple submissions for each assignment.

Kaggle

Kaggle is where we test your understanding and ability to extend neural network architectures discussed in the lectures, particularly for the Part 2s of the homework assignments. Each Kaggle competition (HW Part 2s) has a leaderboard where you can evaluate your model performance compared to your classmates. You can make upto 10 submissions each day for every assignment, the highest score will be used for grading.

MediaServices/YouTube

CMU students who are not in the live lectures should watch the uploaded lectures at MediaServices in order to get attendance credit. Links to individual videos will be available in the Schedule of Lectures table as they are uploaded.

Our YouTube Channel is where non-CMU folks can view all lectures and recitation recordings.

Books and Other Resources

The course will not follow a specific book, but will draw from a number of sources. We list relevant books at the end of this page. We will also put up links to relevant reading material for each class. Students are expected to familiarize themselves with the material before the class. The readings will sometimes be arcane and difficult to understand; if so, do not worry, we will present simpler explanations in class.

You can also find a nice catalog of models that are current in the literature here. We expect that you will be in a position to interpret, if not fully understand many of the architectures on the wiki and the catalog by the end of the course.

Academic Integrity

You are expected to comply with the University Policy on Academic Integrity and Plagiarism.
  • You are allowed to talk with and work with other students on homework assignments.
  • You can share ideas but not code. You should submit your own code.
Your course instructor reserves the right to determine an appropriate penalty based on the violation of academic dishonesty that occurs. Violations of the university policy can result in severe penalties including failing this course and possible expulsion from Carnegie Mellon University. If you have any questions about this policy and any work you are doing in the course, please feel free to contact your instructor for help.