Professor
Kai-Wei Chang
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Most Helpful Review
Fall 2019 - This class was hard. It was very math-heavy and filled with proofs. If you are not super familiar with the material like I was, prepare to spend a lot of time trying to understand what is going on outside of class. Kai-Wei didn't do a great job explaining any of the concepts that we went over and could be quite confusing when explaining the math behind different models. There are only four problem sets in the course, but they can take a bit of time to do, so the workload isn't too bad for the most part. The exam questions are generally a little bit easier than the homework questions, but there is a lot of probability related questions on exams. The curve for the class this quarter was as follows (He won't curve down only up): A+ 11, A 33, A- 33, B+ 35, B 22, B- 23, C+ 14, C 14, Other 6 (# of people per grade not %). Although the material was pretty challenging and Kai-Wei didn't do an excellent job explaining it, I found the class to be semi-interesting. I thought it was cool to understand what machine learning really is and what goes into making a model. PAC Theory was especially interesting in my opinion!
Fall 2019 - This class was hard. It was very math-heavy and filled with proofs. If you are not super familiar with the material like I was, prepare to spend a lot of time trying to understand what is going on outside of class. Kai-Wei didn't do a great job explaining any of the concepts that we went over and could be quite confusing when explaining the math behind different models. There are only four problem sets in the course, but they can take a bit of time to do, so the workload isn't too bad for the most part. The exam questions are generally a little bit easier than the homework questions, but there is a lot of probability related questions on exams. The curve for the class this quarter was as follows (He won't curve down only up): A+ 11, A 33, A- 33, B+ 35, B 22, B- 23, C+ 14, C 14, Other 6 (# of people per grade not %). Although the material was pretty challenging and Kai-Wei didn't do an excellent job explaining it, I found the class to be semi-interesting. I thought it was cool to understand what machine learning really is and what goes into making a model. PAC Theory was especially interesting in my opinion!
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