CS 451  Machine Learning  Fall 2017 


Prerequisites: CS 200, CS 201, and familiarity with matrix math (or willingness to pick it up on your own)
Week  Topic 
1  Linear regression, linear algebra review, Matlab 
2  Logistic regression, regularization 
3, 4  Neural nets, backpropagation 
5, 6  Bias vs. variance, ML system design and diagnosis 
[Wed 10/18  Midterm exam, 7pm] 
7  Support vector machines 
8  Kmeans, principal component analysis 
9  Anomaly detection, recommender systems 
10, 11  Deep learning 
12  Final projects 
Your final grade will be based on quizzes (15%), homework and programming assignments (40%), final project (10%), a midterm exam (15%), and a final exam (20%). The midterm exam is scheduled for Wednesday, October 18, 7:009:00pm. The final exam will be selfscheduled.
Unless otherwise instructed, feel free to discuss problem sets with other students and exchange ideas about how to solve them. However, there is a thin line between collaboration and plagiarizing the work of others. Therefore, it is required that you must compose your own solution to each assignment. It is unacceptable (1) to solve a problem together and turn in two copies of the same solution or (2) to copy solutions written by your classmates. This implies that you should never have in your possession a copy of all or part of another student's work. It is your own responsibility to protect your work from unauthorized access. If an assignment (or part of one) is designated a group project, then the above rules apply to a group. That is, you are allowed to collaborate on the assignment with your partner(s), but work with others is restricted as discussed above. All exams, of course, must be entirely your own work and you may not collaborate with anyone.
When working on homework problems, it is perfectly reasonable to consult public literature (books, articles, etc.) for hints, techniques, and even solutions. However, you must reference any sources that contribute to your solution. It is also OK to borrow code from the textbook, from materials discussed in class, and from other sources as long as you give proper credit. Assignments and solutions from previous terms are not considered to be part of the "public" literature, and consulting problem set solutions from previous terms constitutes a violation of the Honor Code.
If you are uncertain how the Honor Code applies to a particular assignment, please ask me. The Department of Computer Science takes the Honor Code seriously. Violations are easy to identify and will be dealt with promptly.