Professor
Jonathan Kao
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Most Helpful Review
Fall 2024 - Professor Kao was honestly a little overhyped. In terms of teaching it was pretty standard he would just go over proofs during lecture that often became math heavy. He seemed nice and considerate after our midterm with an average "lower than expected" and let us replace the midterm grade with our final. However, he only gave us false hope; the final was alot harder than the midterm with an average being around 20 percent lower. I felt like the question asked on the final were obscure and a little unfair given the last four years finals had similar format. Alot of the final also depended on thinking about a specific application that wasn't really emphasized. Also the grading rubric for the test was a bit questionable as it wanted us to solve the questions in a very specific way. Class was pretty interesting getting to learn about filters was pretty fun.
Fall 2024 - Professor Kao was honestly a little overhyped. In terms of teaching it was pretty standard he would just go over proofs during lecture that often became math heavy. He seemed nice and considerate after our midterm with an average "lower than expected" and let us replace the midterm grade with our final. However, he only gave us false hope; the final was alot harder than the midterm with an average being around 20 percent lower. I felt like the question asked on the final were obscure and a little unfair given the last four years finals had similar format. Alot of the final also depended on thinking about a specific application that wasn't really emphasized. Also the grading rubric for the test was a bit questionable as it wanted us to solve the questions in a very specific way. Class was pretty interesting getting to learn about filters was pretty fun.
Most Helpful Review
Spring 2023 - I love Jonathan Kao. His lectures are very clear—with amazing annotated notes. Concepts that may seem confusing—Kao has a unique ability to make them seem approachable and common sense-like. In office hours, he is always willing to take questions, talk about the course, or just life in general. I've had great conversations with him regarding the existence of free will. Not many professors are that engaged with their students. One minor criticism I have of Kao is how he takes questions in lecture. He indulges in almost every single question, which slows down lecture tremendously. It's great he wants to resolve any unanswered questions, but it's just too many. (It's also evident that some students ask questions just to make them seem smarter to the professor, but that's another concern.) I feel like the professor can fix this by setting expectations for questions at the beginning of the course. If you feel like your question helps everyone in class, feel free to ask it in lecture. If not, ask it during office hours. Overall though, great professor. I love Tonmoy Monsoor. Super knowledgeable TA, always willing to help during discussion, holds great review sessions.
Spring 2023 - I love Jonathan Kao. His lectures are very clear—with amazing annotated notes. Concepts that may seem confusing—Kao has a unique ability to make them seem approachable and common sense-like. In office hours, he is always willing to take questions, talk about the course, or just life in general. I've had great conversations with him regarding the existence of free will. Not many professors are that engaged with their students. One minor criticism I have of Kao is how he takes questions in lecture. He indulges in almost every single question, which slows down lecture tremendously. It's great he wants to resolve any unanswered questions, but it's just too many. (It's also evident that some students ask questions just to make them seem smarter to the professor, but that's another concern.) I feel like the professor can fix this by setting expectations for questions at the beginning of the course. If you feel like your question helps everyone in class, feel free to ask it in lecture. If not, ask it during office hours. Overall though, great professor. I love Tonmoy Monsoor. Super knowledgeable TA, always willing to help during discussion, holds great review sessions.
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Most Helpful Review
Winter 2022 - I don't have anything to say that others haven't already said, Professor Kao is truly one of the best lecturers at UCLA and I would highly recommend this class if you are interested in Neural Networks and Deep Learning. Also, the TAs for this class were amazing, especially Tonmoy Monsoor. Tonmoy is insanely knowledgeable about the topic and his discussions were super useful for the homeworks! Grading: Homework: 40% (5 homeworks) Midterm: 30% Final Project: 30% Extra Credit: 0.5% for filling out class eval, up to 1.5% for participating on piazza (in a useful way), and some extra credit given on the midterm (final question on the exam is optional extra credit)
Winter 2022 - I don't have anything to say that others haven't already said, Professor Kao is truly one of the best lecturers at UCLA and I would highly recommend this class if you are interested in Neural Networks and Deep Learning. Also, the TAs for this class were amazing, especially Tonmoy Monsoor. Tonmoy is insanely knowledgeable about the topic and his discussions were super useful for the homeworks! Grading: Homework: 40% (5 homeworks) Midterm: 30% Final Project: 30% Extra Credit: 0.5% for filling out class eval, up to 1.5% for participating on piazza (in a useful way), and some extra credit given on the midterm (final question on the exam is optional extra credit)
Most Helpful Review
Fall 2022 - This is a interesting seminar that introduces you to the research of biomedical devices that interface directly with neurons (brain machine interfaces or BMIs), and you get to hear Kao discuss about his research as well. The workload is very light, lecture notes are posted on BruinLearn, and only has a final project (fairly easy to complete) assigned during the last two weeks of the quarter that for my year is completed in MATLAB (Kao has plans to update this to Python like he did for assignments for his ECE 102 class).
Fall 2022 - This is a interesting seminar that introduces you to the research of biomedical devices that interface directly with neurons (brain machine interfaces or BMIs), and you get to hear Kao discuss about his research as well. The workload is very light, lecture notes are posted on BruinLearn, and only has a final project (fairly easy to complete) assigned during the last two weeks of the quarter that for my year is completed in MATLAB (Kao has plans to update this to Python like he did for assignments for his ECE 102 class).
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Most Helpful Review
Spring 2023 - A great course with a great lecturer and TAs. The lectures are well prepared and Prof. Kao is really good at teaching. He's happy to stop anytime and answer your questions. TAs are very helpful in the discussions and OH. The exams are fair, and do please attend the midterm and final review held by the TA! The topics are very similar to what will appear in the exam so you definitely should spend enough time reviewing these topics. If you are interested in the neuroscience and have a strong knowledge base of probability, linear algebra and Python, the course is a perfect choice. A little bit of matrix calculus is involved but truse me, they just look scary. 40% 6 homeworks, 25% midterm, 35% final.
Spring 2023 - A great course with a great lecturer and TAs. The lectures are well prepared and Prof. Kao is really good at teaching. He's happy to stop anytime and answer your questions. TAs are very helpful in the discussions and OH. The exams are fair, and do please attend the midterm and final review held by the TA! The topics are very similar to what will appear in the exam so you definitely should spend enough time reviewing these topics. If you are interested in the neuroscience and have a strong knowledge base of probability, linear algebra and Python, the course is a perfect choice. A little bit of matrix calculus is involved but truse me, they just look scary. 40% 6 homeworks, 25% midterm, 35% final.
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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