MSSP 608: Practical Machine Learning Methods

This course prepares me to use tools from those fields effectively in applied contexts and build skills including (1) feature representations of spreadsheet-based or text datasets; (2) training classification and regression models for prediction tasks; (3) evaluation of machine learning model accuracy and error analysis; and (4) reasoning about predictive models and making tradeoffs like bias vs. variance, granularity and annotation complexity in labeled training data, and the ethical application of predictive modeling to human-centered data.

August 30 – December 15, 2021

2:15 PM – 2:45 PM

Philadelphia, United States