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Fabien Scalzo
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Highly recommend Prof. Scalzo. Really nice guy, and he does a good job of explaining concepts. I believe this class is now a regular CS class and not a 188 anymore, but when I took it basically all you did was a quarter long project and a final exam. The final was just memorization of concepts covered in his slides, and for the project you could pretty much do anything with machine learning and medical data. So the workload was basically up to you: you could either just do a really simple project, or if you had a personal interest you could go for something more ambitious. Either way I think he tended to grade on the easier side, especially if he saw you were putting effort into it. Highly recommend this class if you want to learn about machine learning with medical imaging and do a practical project.
This is for computer vision which is quite different from the medical devices class. It was the first time being taught so at times was heavily disorganized and the other professors and TAs could be unhelpful. Not really sure what was going on in class. The pacing seemed off too. Midterm was easy, final was hard. At the end of it, I'm still not sure what I learned. Scalzo is pretty nice though, the class was just poorly run.
Prof. Scalzo is easily one of the best cs professors I've ever had here at UCLA. He did a really good job explaining hard concepts. And generally, Prof. Scalzo is a very nice guy. Patient and very helpful.
Overall this is a pretty chill class but you also learn a lot. You don't have to have ML experience coming into the class, and don't have to start working on the final project until Scalzo covers ML in class, which is nice. Workload is a couple homework assignments done in Google Colab using Python libraries to do image processing and stuff, plus the group project. Some of the homework problems seem tricky but the TAs do demos with extremely similar problems in discussion so it ends up being pretty straightforward.
Most of the grade is the group project, which you work on for the later half of the quarter. You have a lot of leeway in choosing your topic and can have an advisor to help (mine was Scalzo and he was really good about explaining each part of the project and giving feedback on our progress). Scalzo doesn't grade it too strictly, but you do have to put effort into it.
Professor Scalzo is a mensch
Highly recommend Prof. Scalzo. Really nice guy, and he does a good job of explaining concepts. I believe this class is now a regular CS class and not a 188 anymore, but when I took it basically all you did was a quarter long project and a final exam. The final was just memorization of concepts covered in his slides, and for the project you could pretty much do anything with machine learning and medical data. So the workload was basically up to you: you could either just do a really simple project, or if you had a personal interest you could go for something more ambitious. Either way I think he tended to grade on the easier side, especially if he saw you were putting effort into it. Highly recommend this class if you want to learn about machine learning with medical imaging and do a practical project.
This is for computer vision which is quite different from the medical devices class. It was the first time being taught so at times was heavily disorganized and the other professors and TAs could be unhelpful. Not really sure what was going on in class. The pacing seemed off too. Midterm was easy, final was hard. At the end of it, I'm still not sure what I learned. Scalzo is pretty nice though, the class was just poorly run.
Prof. Scalzo is easily one of the best cs professors I've ever had here at UCLA. He did a really good job explaining hard concepts. And generally, Prof. Scalzo is a very nice guy. Patient and very helpful.
Overall this is a pretty chill class but you also learn a lot. You don't have to have ML experience coming into the class, and don't have to start working on the final project until Scalzo covers ML in class, which is nice. Workload is a couple homework assignments done in Google Colab using Python libraries to do image processing and stuff, plus the group project. Some of the homework problems seem tricky but the TAs do demos with extremely similar problems in discussion so it ends up being pretty straightforward.
Most of the grade is the group project, which you work on for the later half of the quarter. You have a lot of leeway in choosing your topic and can have an advisor to help (mine was Scalzo and he was really good about explaining each part of the project and giving feedback on our progress). Scalzo doesn't grade it too strictly, but you do have to put effort into it.