Features are properties that are used as inputs to a machine learning model. For instance, a recommendation application might use the total amount per purchase or product category as one of its many features. Generating a new feature, called feature engineering, takes a tremendous amount of work. The same features must be used both for training, based on historical data, and for the model prediction based on the online or real-time data. This creates a significant additional engineering effort, and leads to model inaccuracy when the online and offline features do not match. Furthermore, monitoring solutions must be built to track features and results and send alerts of data or model drift.

The Iguazio integrated feature store, at the heart of its data science and MLOps platform, solves those challenges. Accelerate the development and deployment of AI applications with automated feature engineering, improved accuracy, feature sharing and glueless integration with training, serving and monitoring frameworks.