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.Documentation Index
Fetch the complete documentation index at: https://kumo.ai/docs/llms.txt
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Learn More:
- How do I use a feature store?
- What model architecture does Kumo incorporate into its GNN design search space?