COMPSCI 282BR: Topics in Machine Learning: Interpretability and Explainability

COMPSCI 282BR: Topics in Machine Learning: Interpretability and Explainability

Syllabus and all the other logistics for this course are here: 282BR_Details

 

Prerequisites: Students are expected to be fluent in basic linear algebra, probability, algorithms, and machine learning (at the level of CS181). Students are also expected to have programming and software engineering skills to work with data sets using Python, numpy, and sklearn. 

 

 

Course Summary:

Date Details