CPSC 66: Machine Learning — Fall 2024

For Fall 2024, please use the following waitlist procedure to stay active in the course and to be considered for open positions:

All the required readings will be available online for free. Some of the 'optional supplement' texts may only exist in paper form, but copies of these will be on reserve at the library.

We will utilize A Course in Machine Learning by Hal Daume III as our primary text. It is an online, free ebook.

Note that this book is only available in PDF form; if you want a hard copy, you should be able to get printouts made using TAP funds. Please let me know if you have any difficulties with this.

We will also use Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani, and Jerome Friedman. We will be using this book (again, available for free online) for several supplementary readings on topics that CIML doesn’t cover in as much detail as I would like.

By the end of the course, you will understand:

I have outlined the skills and objectives this course promises to provide you. For these promises to be upheld, you will need to commit to the policies outlined below. To succeed you should:

This is subject to change but is a rough estimate

As discussed in responsibilities, your participation involves:

Partnerships where partners work mostly independently rarely work out well and frequently fail to produce complete, correct and robust solutions. More importantly, they don’t result in both partners learning well, which is ultimately the point of doing the work in the first place. Partnerships where partners work side-by-side for all or most of the time tend to work out very well, with both partners learning (and accomplishing) more than they would alone.

You and your partner are both equally responsible for initiating scheduling times when you can meet to work together, and for making time available in your schedule for working together.

For partnered lab assignments, you should follow these guidelines:

Taking time up front to design a plan for your solution together and to doing incremental implementation and testing together may seem like it is a waste of time, but in the long run it will save you a lot of time by making it less likely that you have design or logic errors in your solution, and by having a partner to help track down bugs and to help come up with solutions to problems.

Academic honesty is required in all your work. Under no circumstances may you hand in work done with or by someone else, or produced by an algorithm, without making the source of the work explicitly clear.

Discussing ideas and approaches to problems with others on a general level is encouraged, but you should never share your solutions with anyone else nor allow others to share solutions with you. You may not examine solutions belonging to someone else, nor may you let anyone else look at or make a copy of your solutions. This includes, but is not limited to, obtaining solutions from students who previously took the course or solutions that can be found online. You may not share information about your solution in such a manner that a student could reconstruct your solution in a meaningful way (such as by dictation, providing a detailed outline, or discussing specific aspects of the solution). You may not share your solutions even after the due date of the assignment.

In your solutions, you are permitted to include material which was distributed in class, material which is found in the course textbook, and material developed by or with an assigned partner. In these cases, you should always include detailed comments indicating on which parts of the assignment you received help and what your sources were.

The use of generative AI tools (e.g. chatGPT, GitHub CoPilot, etc.) without permission is also considered to be unauthorized collaboration with an outside source and is a violation of our academic integrity policy. If you feel these tools would be appropriate in a given context, feel free to ask the instructor. Note that even if permission is granted, these sources must be properly attributed.

When working on tests, exams, or similar assessments, you are not permitted to communicate with anyone about the exam during the entire examination period (even if you have already submitted your work). You are not permitted to use any resources to complete the exam other than those explicitly permitted by course policy. (For instance, you may not look at the course website during the exam unless explicitly permitted by the instructor when the exam is distributed.) You may also not communicate detailed information about exams (e.g. questions, solutions) to anyone not taking the course at the same time as you (i.e. don’t share exams with students taking the course a different semester).

Failure to abide by these rules constitutes academic dishonesty and will lead to a hearing of the College Judiciary Committee. According to the Faculty Handbook:

This policy applies to all course work, including but not limited to code, written solutions (e.g. proofs, analyses, reports, etc.), exams, and so on. This is not meant to be an enumeration of all possible violations; students are responsible for seeking clarification if there is any doubt about the level of permissible communication.

Any code, text, or content not created exclusively by you and used without attribution is plagiarism. This is true regardless of whether the original source was a scholarly text, another student, an online platform (e.g. StackOverflow), or a generative model (e.g. ChatGPT). Using resources such as these may be appropriate under some circumstances, and not under others, but regardless you must always properly acknowledge and cite the source of the information. When in doubt, add a statement of attribution! In addition, when using any type of generative AI, you must also describe how it was used, e.g. by giving the prompt.

Here are some examples of what this might look like:

For lab assignments, each student may use up to a total 3 late days across the entire semester, no questions asked. Late days do not apply to homework, quizzes, or other forms of assessment. A late day is a considered a full 24-hours (i.e., 15 minutes late is the same as 23 hours late) and late days are counted against all lab partners.

To use your late days, you must make a private Ed post to Instructors after you have completed the lab and pushed to your repository. You do not need to inform anyone ahead of time, and you do not need to provide a reason. When you use late days, you should still expect to work on the newly-released lab during the following lab section meeting. The professor will always prioritize answering questions related to the current lab assignment during lab meetings and office hours. In the rare case in which only one partner has unused late days, the partnership can use the late days, barring a consistent pattern of abuse.

If you feel that you need an extension on an assignment or that you are unable to attend class for two or more meetings due to a medical condition (e.g., extended illness, concussion, hospitalization) or other emergency, you must contact the dean’s office and your instructors. Faculty will coordinate with the deans to determine and provide the appropriate accommodations. Note that for illnesses, the College’s medical excuse policy, states that you must be seen and diagnosed by the Worth Health Center if you would like them to contact your class dean with corroborating medical information.

If you believe you need accommodations for a disability or a chronic medical condition, please visit the Student Disability Services website for details about the accommodations process. Since accommodations require early planning and are not retroactive, contact Student Disability Services as soon as possible. You are also welcome to contact me privately to discuss your academic needs. However, all disability-related accommodations must be arranged, in advance, through Student Disability Services.

To receive an accommodation for a course activity you must have an official Accommodations Letter and you need to meet with me to work out the details of your accommodation at least two weeks prior to any activity requiring accommodations.