Overview

Welcome to the Grocery SDK Tutorials.

This tutorial series walks you through creating a catalog, registering its data model, formulating your use case, crafting features and computing training data. All using FeatureByte SDK.

For deploying and managing those features using SDK, join the Credit Default SDK Tutorials.

Dataset Overview

The dataset contains four tables containing data from a chain of grocery stores:

• GROCERYCUSTOMER: Customer details, including their name, address, and date of birth.

• GROCERYINVOICE: Grocery invoice details, containing the timestamp and the total amount of the invoice.

• INVOICEITEMS: The grocery item details within each invoice, including the quantity, total cost, discount applied, and product ID.

• GROCERYPRODUCT: The product group description for each grocery product.

Tutorial Workflow

1. Create catalog

Define the Data Model of the catalog

2. Register tables

3. Register entities

4. Update descriptions to tables (optional)

5. Set Default Cleaning Operations

Formulate your use case

6. Formulate Use Case

7. Create Observation Tables

Create features

8. Create lookup feature

9. Create window aggregate features

10. Derive features from other features

11. Derive similarity features from bucketing

12. Use embeddings

Compute training data for your use case

13. Create feature list

14. Compute historical feature values

Download the tutorials here

Download all the Grocery Notebooks Tutorial notebooks here