EC ENGR C143A
Neural Signal Processing and Machine Learning
Description: Lecture, four hours; discussion, one hour; outside study, seven hours. Requisite: course 131A, Mathematics 33A. Topics include fundamental properties of electrical activity in neurons; technology for measuring neural activity; spiking statistics and Poisson processes; generative models and classification; regression and Kalman filtering; principal components analysis, factor analysis, and expectation maximization. Concurrently scheduled with course C243A. Letter grading.
Units: 4.0
Units: 4.0
1 of 1
Most Helpful Review
Fall 2025 - the workload is a bit rough, especially when your taking 2 CS classes concurrently. I would have two projects due, one for this class and another for a different CS class. So in total I would be spending 30+ hours on projects. The week that both my projects were due, I was in hell and pulling all nighters (maybe my fault for not starting ahead of time). But Jonathan Kao is very generous with his late days (4 days) for homework assignments. The content itself was pretty difficult, but honestly I am not a huge math person, so concepts were difficult for me to grasp. The professor had to be the best at explaining though, because I was able to get by with an 81 on the final, the mean was a 90 (and still managed to get an A in the class). This just shows that Professor Kao cares way more about learning, then the actual grade he gives his students. We get a project at the end for our final, so it was a lot easier to clutch in the end. Just the beginning of the quarter, is a bit rough starting out with this class....I seriously thought I was not going to make it.
Fall 2025 - the workload is a bit rough, especially when your taking 2 CS classes concurrently. I would have two projects due, one for this class and another for a different CS class. So in total I would be spending 30+ hours on projects. The week that both my projects were due, I was in hell and pulling all nighters (maybe my fault for not starting ahead of time). But Jonathan Kao is very generous with his late days (4 days) for homework assignments. The content itself was pretty difficult, but honestly I am not a huge math person, so concepts were difficult for me to grasp. The professor had to be the best at explaining though, because I was able to get by with an 81 on the final, the mean was a 90 (and still managed to get an A in the class). This just shows that Professor Kao cares way more about learning, then the actual grade he gives his students. We get a project at the end for our final, so it was a lot easier to clutch in the end. Just the beginning of the quarter, is a bit rough starting out with this class....I seriously thought I was not going to make it.
1 of 1
