Store, reuse, and share machine learning features
A central feature registry makes it easy for users to find, define, and incorporate features to accelerate model and application development. Cataloging and search capabilities increase experimentation, standardization, and collaboration across teams.
Over 200 pre-built functions give users a head start on experimentation and application development. Promote reusability by first defining and storing features, along with the associated metadata, and then committing those features to the central registry for other users to find and use.
Serve ML models with up-to-date data as needed. By separating the data pipelines from the ML models, C3 AI Platform allows even large aggregation-based and compute heavy features to be served to models immediately, ensuring that all predictions and insights are timely and relevant.
Feature lineage plays a vital role in helping teams scale their machine learning practice. Data science teams can leverage end-to-end lineage that documents relationships between features, models, and data snapshots to enable model and experiment reproducibility at scale.
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