This tutorial demonstrates the use of Feast as part of a real-time credit scoring application.
- The primary training dataset is a loan table. This table contains historic loan data with accompanying features. The dataset also contains a target variable, namely whether a user has defaulted on their loan.
- Feast is used during training to enrich the loan table with zipcode and credit history features from a S3 files. The S3 files are queried through Redshift.
- Feast is also used to serve the latest zipcode and credit history features for online credit scoring using DynamoDB.
- Terraform (v1.0 or later)
- AWS CLI (v2.2 or later)
In order to get started with this tutorial you can open the Feature_Store.ipynb file and follow the steps.
Happy Coding!