Undergraduate Prerequisites: (ENGEK103 & ENGEK125 & ENGEK381) - Linear regression. Maximum likelihood and maximum a posteriori estimation. Classification techniques, including na?ve Bayes, k-nearest neighbors, logistic regression, and support vector machines. Data visualization and feature extraction, including principal components analysis and linear projections. Clustering. Introduction to neural networks and deep learning. Discussion of other modern analysis methods.
FALL 2024 Schedule
Section |
Instructor |
Location |
Schedule |
Notes |
A1 |
Saligrama |
CDS B62 |
MW 2:30 pm-4:15 pm |
If EC 414 is closed, the waitlist is: https://ece.wufoo.com/forms/sc5k6wl1xoqjyf/ |
FALL 2024 Schedule
Section |
Instructor |
Location |
Schedule |
Notes |
B1 |
Saligrama |
MUG 205 |
F 10:10 am-11:00 am |
|
FALL 2024 Schedule
Section |
Instructor |
Location |
Schedule |
Notes |
B2 |
Saligrama |
MUG 205 |
F 12:20 pm-1:10 pm |
|
Note that this information may change at any time. Please visit the MyBU Student Portal for the most up-to-date course information.