The class is centered around 6 topics: (1) ML for ER; (2) ML for data cleaning; (3) data profiling for ML and data management; (4) training data labeling for ML; (5) cleaning for ML; and (6) interpretation for ML
Disclaimer: The schedule could be subject to
change as the semester progresses.