Suhas Diggavi is very bright and truly an accomplished computer engineer. His lectures are very clear, but can get a little too deep into confusing notation. However, this notation is what's used in machine learning literature, so I can't exactly fault him for using it—does prepare us for actual ML readings well.

The course taught cool concepts, albeit a little slowly. I spoke with another ML professor (Jonathan Kao) about the course content, and he says that some of it is not very useful (KNN). Not really an indictment on the professor, but more so on the curriculum.

What's great is how small the class was. Only 19 students are enrolled, and only about 7 attend lecture. Very interactive and immersive learning experience.

Rida is a great TA. Very knowledgeable, fills in gaps that were present in lecture, and always is willing to expand on concepts.

Similar to lecture, not many people attend discussion (only 3 including myself). This makes it more like an office hour where we can interact with the TA very well. Would 100% recommend Rida.