Implements DFS for automated feature engineering.
It works to prepare raw relational and transactions datasets for machine learning or predictive modeling.
Includes a collection of reusable feature engineering functions for a wide range of domains.
Allows for user-defined primitives to encourage automation, reuse across projects, and community collaboration.
Easily integrated in to existing production data pipelines.
Designed to work with common frameworks like Pandas for data preparation or scikit-learn for machine learning.
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