Professional Graduate Data Science Coursework - Fall semester 2016
The course was the first part of a series about advanced data science methods. Topics include the analysis of high dimensonal data with linear methods such as lasso and ridge regression, bayesian modeling and sentiment analysis as well ensemble methods such as bagging and boosting. Most of the programming was done in Python
The directory structure is as follows:
| DIRECTORY | DESCRIPTION |
|---|---|
. |
Files such as README and gitignore |
./hw/ |
The homework project files |
./labs/ |
Material from the labs |
./lectures/ |
Material from the lectures |
./midterm/ |
Material from the midterms |
./project/ |
Material from the final project |
./videos/ |
Videos from the lectures and labs |
You can access all the coursework etc. here.