DataRobot unveiled upgrades to every product in its enterprise AI platform to optimize the value seen through AI deployments and enable better business outcomes with AI. Enhancements include:
- MLOps remote model challengers, which allow organizations to challenge any production model – no matter where it is running and regardless of the framework or language in which it was built. By analyzing how challenger models perform versus the current champion model on the exact same production data, companies can easily determine which model is best for them now or at any point in history.
- Choose your own forecast baseline, which lets companies compare the output of their forecasting models with predictions from DataRobot’s Automated Time Series product.
- Visual AI image augmentation, available through DataRobot AutoML, which creates new training images from a company’s dataset by intelligently replicating and transforming the original images. Organizations can improve the accuracy of their image models while reducing the need to manually capture and label new images.
- Enhanced prediction preparation. DataRobot’s visual data prep capabilities allow organizations to prepare their data for model training. Customers can use visual data prep to more easily score new data from models already deployed. DataRobot’s Data Prep tools work within platform, enabling companies to secure scored data and prediction explanations from any deployed model for transparency and trusted AI. For addition features see