Course 3A: Time Series in Driverless AI

Learning Outcomes:

By the end of this training, the attendee will be able to

• Create and tune a predictive model with a time component
• Explain what is meant by a “gap” and determine its value for a given problem
• Locate and explain expert settings related to time series models
• Incorporate additional time series models, transformers, and scorers via recipes
• Compare multiple models side-by-side and find Shapley values for predictions

Prerequisites

This course assumes 

• Completion of “Introduction to Driverless AI” or equivalent experience.
• Completion of “Customizing Driverless AI with Recipes.”
• Familiarity with statistical or machine learning modeling.
• Prior experience with Time Series models preferred, but not required.