The best aspects of the course included the helpful and wel -designed homework assignments, as well as well the interesting and applicable material that students learned. The professor was very knowledgeable and showed lots of enthusiasm in teaching the subject. The worst aspects of the course included the hefty workload, and lack of guidance on the projects. The course would improve if there was a well-defined course syl abus and better discussions/assignments to help students understand what they were really learning. Prospective students should endeavor to stay on top of the work, and

The best aspects of the course included the broad survey of statistical machine learning and the exposure to cutting edge discoveries in the field. Some students noted that the professor was engaging and open to discussion during class, and that the lecture slides and assignments provided were effective teaching tools. Some students felt that the course was not wel planned and did not al ot enough time to cover other areas of machine learning. Suggestions for improvement included having lecture twice per week, and being more selective about which topics are best addressed in class or saved for self-study. Prospective students should be aware that this is a theory-focused course without application or coding, and should have a strong background in linear algebra.