Academic Events Notebooks

These guides consist of the following three Jupyter notebooks:

• Part 1: Data Engineering shows you how to call the Events API to extract the Academic Events data to a DataFrame.

• Part 2: Data Exploration is a guide to exploring PredictHQ's Academic Events data for Data Science teams.

• Part 3: Feature Engineering provides examples of how to aggregate and extract features from the data.