EC ENGR C147
Neural Networks and Deep Learning
Description: Lecture, four hours; discussion, two hours; outside study, six hours. Requisites: courses 131A, 133A or 205A, and M146, or equivalent. Review of machine learning concepts; maximum likelihood; supervised classification; neural network architectures; backpropagation; regularization for training neural networks; optimization for training neural networks; convolutional neural networks; practical CNN architectures; deep learning libraries in Python; recurrent neural networks, backpropagation through time, long short-term memory and gated recurrent units; variational autoencoders; generative adversarial networks; adversarial examples and training. Concurrently scheduled with course C247. Letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Winter 2024 - I think the winter 2024 offering of C147 was very similar to the reviews I've read in the past: - There were some very hard/long assignments. However if you used Piazza you should be fine - The class was a bit more mathy in the beginning than compared to the end - The professor was excellent! There are also several comments complaining about the "slow pace" of the class, "over-enrollment" and new 50% Midterm Weight. I'd like to address those and what my views are as a fellow student: Personally, as someone who skipped M146 and went straight into C147, I appreciated that the professor reviewed some of the more fundamental aspects of DL in the beginning of the course. Furthermore, I'd like to point out that this is after all, a graduate class. Grad Students often don't get to take the particular sequence of courses at UCLA prior to coming here, so it make sense that the professor do some review in the very beginning to make sure everyone is on the same page. For those that were interested in "practical" machine learning (ie learning one of the popular ML libs), the final project was an opportunity to do that. Personally, I think this class is not a torch-bootcamp and rightfully so: C147 focus on more fundamental knowledge and the theory side of DL. There are also other more coding-heavy classes offered (CS188 in W24 for example) that one can take to gain that kind of experience. While it is true this was a very big class, personally between taking the class vs not taking the class I'd always choose the former. I definitely appreciated the effort the teaching staff put into making the logistics work for such a large class! Finally, the median for the class was an A- (partly due to grad class, also because Kao doesn't grade harsh). I really don't understand why people complain about grades at this point considering this is an upper-div and the midterm median was a B.
Winter 2024 - I think the winter 2024 offering of C147 was very similar to the reviews I've read in the past: - There were some very hard/long assignments. However if you used Piazza you should be fine - The class was a bit more mathy in the beginning than compared to the end - The professor was excellent! There are also several comments complaining about the "slow pace" of the class, "over-enrollment" and new 50% Midterm Weight. I'd like to address those and what my views are as a fellow student: Personally, as someone who skipped M146 and went straight into C147, I appreciated that the professor reviewed some of the more fundamental aspects of DL in the beginning of the course. Furthermore, I'd like to point out that this is after all, a graduate class. Grad Students often don't get to take the particular sequence of courses at UCLA prior to coming here, so it make sense that the professor do some review in the very beginning to make sure everyone is on the same page. For those that were interested in "practical" machine learning (ie learning one of the popular ML libs), the final project was an opportunity to do that. Personally, I think this class is not a torch-bootcamp and rightfully so: C147 focus on more fundamental knowledge and the theory side of DL. There are also other more coding-heavy classes offered (CS188 in W24 for example) that one can take to gain that kind of experience. While it is true this was a very big class, personally between taking the class vs not taking the class I'd always choose the former. I definitely appreciated the effort the teaching staff put into making the logistics work for such a large class! Finally, the median for the class was an A- (partly due to grad class, also because Kao doesn't grade harsh). I really don't understand why people complain about grades at this point considering this is an upper-div and the midterm median was a B.
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