DataRobot Updates its AI Platform with DataRobot Paxata Integration

DataRobot Updates its AI Platform with DataRobot Paxata Integration

Source: DataRobot on YouTube

DataRobot has announced a series of updates to its enterprise AI platform, headlined by the integration of DataRobot Paxata data preparation. Other enhancements include the addition of new AI applications, automated deep learning functionality, and visual AI. This release comes on the heels of DataRobot’s December acquisition of Paxata. The teams at both companies have been working to make AI-based data preparation a reality for the solution in 2020, and it appears this represents the completion of that process.

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DataRobot Paxata is integrated with the platform’s AI catalog so users can explore, clean, combine and shape data for training and deploying machine learning models. Any machine learning model can be turned into an AI application. The AI applications feature also includes Applications Gallery, a collection of AI applications available to business users.

DataRobot has improved deep learning via the addition of a new Keras-based model framework. The new deep learning features allow users to build models that are ready to deploy into production. DataRobot is also making it easier to understand deep learning models with the infrastructure a user has in place. The tool’s Automated Time Series now includes new deep learning techniques that remove traditional forecasting barriers so users can work on large-scale multi-series forecasting applications.

New visual AI lets users address computer vision use cases and combine diverse data in their models. DataRobot is offering immediate support for use cases requiring image recognition and classification. Users can drag and drop a collection of images into a project and build custom deep learning models. Visual AI then takes image-based machine learning a step further by enabling users to leverage images alongside other feature types.

DataRobot MLOps has been enhanced to include pre-packaged model environments so users can drag-and-drop model files that have been developed in languages like Python and R. Model files can then be deployed via Kubernetes. MLOps also offers Monitoring Agents that can capture metrics from models deployed to almost any environment. The release touts unlimited batch scoring with integrations to leading cloud storage options as well.

Learn more about the new release and DataRobot Paxata integration here.

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Timothy King

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Timothy is Solutions Review's Senior Editor. He is a recognized thought leader and influencer in enterprise BI and data analytics. Timothy has been named a top global business journalist by Richtopia. Scoop? First initial, last name at solutionsreview dot com.
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