The professor is super cool and (at least in lecture) tries his best to keep students engaged. It's obvious that he's really knowledgeable and enjoys what he does. While the content itself can be complex, he structures the class so that it is (in my opinion) easy to get an A. To put this into perspective, I'm a Cogsci major who took this class as an elective and have only took one other Stats upper div, and I managed to get a high A. I still had to put in some effort, but I honestly feel like Stats majors/minors could probably do well in this class with minimal effort. To get an A+, I scored around the average on the homeworks, final, and Kaggle project and around the upper quartile for the midterm.

While caring, the professor was often unclear, and the class itself was extremely disorganized. For some of the slideshows with ~100 slides, he only went over about half of the slides while skimming over the rest. Sometimes information given by the professor and the TA would conflict. While the final project was fun and applicable overall, the professor gave very little guidance for the presentation and the paper--only providing a single "sample" of each from previous quarters. Grading itself was not overly strict, yet it was slightly confusing. On some of the homeworks and the final, grades were reposted multiple times--sometimes going up or going down with little explanation as to the rationale for the changes.

As this was my first machine learning class, I found the content very interesting. It's basically a survey of a whole bunch of supervised and unsupervised machine learning methods. You don't go super in-depth on specific topics, but you do learn a lot. So overall, poorly structured class but cool content and professor.

I took him for Stats 101B and Stats 101C, and honestly, I don't think he's that bad. He is definitely an unclear lecturer, but supplies an abundance of slides (which lack adequate information), so you know what to study (I looked in the textbooks to solidify my understanding of the material). He is unresponsive, but TAs can usually answer most of your questions about homeworks and projects. For 101C, we had a midterm (in-person, VERY fair), a final (take-home, easy), and a group project on Kaggle where teams were ranked by performance (we were around 13/32 and got an A+, so I don't think grading was very harsh). We also had 6 homeworks, which varied in difficulty (all on R). At the end of the day, his tests are pretty easy, his projects are graded nicely, and he cares about his students doing well in his class. Although he is a bad lecturer, don't be afraid to take him!

Almo is my favorite professor that I have taken here (and the stats dept has some excellent professors). He is a bit disorganized, but his lectures are excellent and engaging. He is very approachable outside of class and very nice during office hours. The final project was very interesting and a lot of fun to do. The midterm and final were quite fair, and tested your understanding of the material instead of focusing on pointless calculations. Overall 10/10

Almo is a very caring professor, but I have had (way) better lecturers. Material is very similar to Miles' 102B class (basically Intro to ML). I absolutely got destroyed from the all the exams (probably just me, mean and median were B+ and B- for midterm and final), thus ending with a B+ despite performing very well on the Kaggle project. Exams ask a lot about conceptual stuff and has an actual programming question, but it was the conceptual stuff that throws me off since we don't usually get questions on those in our homework and it was relatively hard to find practice questions.

Dr. Almohalwas is the best professor I have had thus far! The class itself is definitely engaging and really useful since you learned so much! (KNN, logistic regression, LDA, QDA, PCA, GAM,...) He is very clear during lectures and very helpful during office hours. I believe the tests are a bit short and difficult, so one needs to attend lectures and be engaged a lot, but it pays off. The group project is really useful and can be considered real-life applications. Overall, Dr. Almo is great and I have never learned so much useful information in a single class!

Definitely worst of the worst.