Feature backfilling

Backfill a feature group using Prefect and Hopsworks

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Table of contents

1. What is this repo about?
2. How to run this code
3. Wannna build real-world ML products?

What is this repo about?

This repository shows how to backfill historical OHLC feature in a Feature Store (Hopsworks) using an orchestration tool (Prefect).

How to run this code

• Create a Python virtual environment with the project dependencies with

  $ make init
  

• Connect to your Prefect Cloud

  $ prefect cloud login 
  

• Set environment variables necessary to talk to your Hopsworks feature store

  $ . ./set_hopsworks_credentials.sh
  

• Backfill OHLC data for a range of dates (e.g. from 2023-01-01 to 2023-01-31)

  $ make from_day=2023-01-01 to_day=2023-01-31 backfill
  

Wannna build real-world ML products?

Check the Real-World ML Program, a hands-on, 3-hour course where you will learn how to design, build, deploy, and monitor complete ML products.