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- Ying Nian Wu
- STATS M231A
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Loved this class. The professor is super clear and concise in explaining difficult concepts, and it was the first presentation of machine learning concepts where I felt like I truly understood. We went over the basics including linear regression and perceptrons, but we also talked about more recent models including the architecture of diffusion models, transformer models, and even SORA.
Homeworks include theory problems, which are fine if you pay attention to the lectures, and some coding problems to get some practice with the theory. The final exam was essentially like the last homework.
Definitely recommend this class to anyone who's interested in learning more deeply about machine learning models.
Loved this class. The professor is super clear and concise in explaining difficult concepts, and it was the first presentation of machine learning concepts where I felt like I truly understood. We went over the basics including linear regression and perceptrons, but we also talked about more recent models including the architecture of diffusion models, transformer models, and even SORA.
Homeworks include theory problems, which are fine if you pay attention to the lectures, and some coding problems to get some practice with the theory. The final exam was essentially like the last homework.
Definitely recommend this class to anyone who's interested in learning more deeply about machine learning models.
Based on 1 User
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