Course 3A: Time Series in Driverless AI
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
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.