What's New?

Release 5.2 of the DataRobot Enterprise AI Platform is truly groundbreaking. It’s packed with new features, including new MLOps capabilities, the next generation of Automated Feature Engineering, a new AI Catalog, and so much more. Here are some of the highlights.

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Machine Learning Operations (MLOps)

Deploy, Manage, and Govern All Your Models
DataRobot MLOps is a new, stand-alone product with support for custom models built using leading frameworks and languages like Python and R. Deploy models onto Kubernetes for high performance and autoscaling advantages. Monitor models deployed anywhere with new monitoring agents and a single monitoring console with advanced data drift detection and popular model metrics.
Read the blog post

Automated Feature Engineering

AI Accelerated Feature Discovery from Related Data
DataRobot accelerates machine learning by automating feature engineering, often considered the most laborious and time-consuming step along the path to value. In this release, we have automated the capability to discover and extract explanatory features from multiple related datasets. This allows you to build better machine learning models in less time and increase the pace of innovation with AI. Read the blog post

AI Catalog

Collaboration for Enterprise AI
The new AI Catalog is tightly integrated with the DataRobot Enterprise AI Platform. AI Catalog helps people to easily find, understand and use the assets they need for their AI projects. It serves as a centralized source of truth for data engineers, data stewards, data scientists, and analysts to gain self-service access to machine learning assets they can trust. Read the blog post

Automated Time Series

New Out-of-the-Box Accuracy and Scaling Strategies
In 5.2, Automated Time Series continues to push out-of-the-box accuracy with several new modeling and scaling strategies. New blueprints consider clusters of series, series-scaled blueprints, mixed forecast distances, and hierarchical modeling strategies. This automates some of the most powerful approaches to time series forecasting. Get started with Automated Time Series

And There's More...

Customers Asked and We Delivered
In addition to the key 5.2 release highlights above, we also added a ton of hot features requested by our customers. These include a word cloud for multi-class models, a new residuals analysis, a DataRobot add-in for Excel, API support for feature fit, and much more. Check out the full list of new features in the 5.2 release notes page in your product documentation.
Contact us for more information

Related resources

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