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Feature Pipeline
Check out Lesson 1 on Medium to better understand how we built the FE pipeline.
Also, check out Lesson 5 to learn how we implemented the data validation layer using Great Expectations.
Install for Development
Create virtual environment:
cd feature-pipeline
poetry shell
poetry install
Check the Set Up Additional Tools and Usage sections to see how to set up the additional tools and credentials you need to run this project.
Usage for Development
To start the ETL pipeline run:
python -m feature_pipeline.pipeline
To create a new feature view run:
python -m feature_pipeline.feature_view
NOTE: Be careful to complete the .env file and set the ML_PIPELINE_ROOT_DIR variable as explained in the Set Up the ML_PIPELINE_ROOT_DIR Variable section of the main README.
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