Professor
Jonathan Kao
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Most Helpful Review
Fall 2018 - I really enjoyed this class with Kao. The concepts are really interesting, and he does a great job of explaining intuition and applications (including to his own research). He is very thorough and doesn't go too fast, and treats the subject with about as much mathematical rigor as you can without being in an actual math class. He created slides in advance, then annotated them in class and posted the annotated PDFs for us to download. I never had to refer to the textbook to understand the material. Kao is also very accommodating to students. He will move office hours, make corrections to materials, email quickly, and is always happy to look up the answer to a question if he does not know the answer already.
Fall 2018 - I really enjoyed this class with Kao. The concepts are really interesting, and he does a great job of explaining intuition and applications (including to his own research). He is very thorough and doesn't go too fast, and treats the subject with about as much mathematical rigor as you can without being in an actual math class. He created slides in advance, then annotated them in class and posted the annotated PDFs for us to download. I never had to refer to the textbook to understand the material. Kao is also very accommodating to students. He will move office hours, make corrections to materials, email quickly, and is always happy to look up the answer to a question if he does not know the answer already.
Most Helpful Review
Spring 2020 - This is the third class I've taken with Professor Kao, having taken his Systems and Signals, and Neural Networks and Deep Learning classes. As always, Kao's lectures are very clear, informative and interesting. The HW can be a bit tricky- start ahead of time and go to office hours. Throughout the quarter, Kao was very accommodating and even relaxed the grading scales at the end of quarter. Due to COVID-19 and remote learning, we weren't able to cover the amount of material the class usually covers. However, for context: the first third of the class covers basic neuroscience, including action potentials and how the brain works. The second third covers Poisson processes and discrete classification. The third half covers decoding including Wiener and Kalman filters, which I think is the most interesting part of the course. If you are looking for an interesting and useful elective, this is the class for you. Highly recommended- 10/10.
Spring 2020 - This is the third class I've taken with Professor Kao, having taken his Systems and Signals, and Neural Networks and Deep Learning classes. As always, Kao's lectures are very clear, informative and interesting. The HW can be a bit tricky- start ahead of time and go to office hours. Throughout the quarter, Kao was very accommodating and even relaxed the grading scales at the end of quarter. Due to COVID-19 and remote learning, we weren't able to cover the amount of material the class usually covers. However, for context: the first third of the class covers basic neuroscience, including action potentials and how the brain works. The second third covers Poisson processes and discrete classification. The third half covers decoding including Wiener and Kalman filters, which I think is the most interesting part of the course. If you are looking for an interesting and useful elective, this is the class for you. Highly recommended- 10/10.
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Most Helpful Review
Winter 2022 - I would highly recommend this class to any interested in deep learning and machine learning. Professor Kao is a very good lecturer and he does an amazing job explaining concepts. I never truly understood how backpropagation worked until he explained it in class. Anyone interested in research/ML should definitely take this class. You will learn so much. However, the class is not a cake walk. It's actually fairly easy to get a good grade in this class as long as you put in the effort. There is only one exam around week 8, which won't be bad if you pay attention to lecture (our average for the exam was a 95%). The homeworks are the real killer and can take a very long time. You essentially have to build neural networks from scratch using Python and Numpy. Overall, this is an amazing class where you can truly learn so much, but at the price of many hours of homework. Professor Kao is probably one of my favorite professors I have ever had at UCLA.
Winter 2022 - I would highly recommend this class to any interested in deep learning and machine learning. Professor Kao is a very good lecturer and he does an amazing job explaining concepts. I never truly understood how backpropagation worked until he explained it in class. Anyone interested in research/ML should definitely take this class. You will learn so much. However, the class is not a cake walk. It's actually fairly easy to get a good grade in this class as long as you put in the effort. There is only one exam around week 8, which won't be bad if you pay attention to lecture (our average for the exam was a 95%). The homeworks are the real killer and can take a very long time. You essentially have to build neural networks from scratch using Python and Numpy. Overall, this is an amazing class where you can truly learn so much, but at the price of many hours of homework. Professor Kao is probably one of my favorite professors I have ever had at UCLA.
Most Helpful Review
Fall 2020 - I took this class as an add-on to ECE 102 with Professor Kao. It was just a one-hour seminar every week and then a project at the end. The project wasn't too bad and just involved some Matlab programming. Overall, I would recommend this seminar if you need some honors credit.
Fall 2020 - I took this class as an add-on to ECE 102 with Professor Kao. It was just a one-hour seminar every week and then a project at the end. The project wasn't too bad and just involved some Matlab programming. Overall, I would recommend this seminar if you need some honors credit.
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Most Helpful Review
Winter 2021 - Be prepared to spend 20+ hours a week on the homework assignments. I learned a ton from this course. It makes it to where AI/ML is not a black box anymore. You can understand how things are working and how it all comes back to the math. The lectures are very good. The professor and TAs are very helpful. It is a great course which I would recommend if you are single and have the time.
Winter 2021 - Be prepared to spend 20+ hours a week on the homework assignments. I learned a ton from this course. It makes it to where AI/ML is not a black box anymore. You can understand how things are working and how it all comes back to the math. The lectures are very good. The professor and TAs are very helpful. It is a great course which I would recommend if you are single and have the time.
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