After creating a project and adding models, dataset templates and datasets, you can trigger feature engineering tasks for your data to ensure the data is pre-processed and transformed in the most efficient way possible. In other words, if your data or model requires some kind of Extract Transform Load (ETL) process, you can achieve this by using feature engineering tasks.
Use the following topics in the Feature Engineering module to organize and facilitate the creation and management of feature engineering tasks.
- Create a new feature engineering task
- Edit a feature engineering task
- View a feature engineering task lifecycle
- Run a feature engineering task
- Approve or reject a feature engineering task
- Deploy a feature engineering task
- Retire a feature engineering task
- Archive a feature engineering task
- Unarchive a feature engineering task