How do I perform feature engineering with Kumo?

Traditional feature engineering is by nature error-prone and time-intensive, requiring considerable time and effort to understand the problem space and the relevant data. Fortunately, Kumo’s state-of-the-art GNN architecture removes the need for computing feature stores and feature engineering pipelines.

By leveraging the relational structure of the entities in the data to build a single enterprise graph, Kumo is able to achieve a comprehensive view of the dynamic interactions and relationships between the different entities in the raw data, without extensive feature engineering or the use of feature stores.

Learn More:

• How do I use a feature store?
• What model architecture does Kumo incorporate into its GNN design search space?