We’re excited to share our first release of the year, DataRobot 7.0. Also check out the DataRobot 7.0 Release webinar (ondemand) to learn more about the release, including:
MLOps remote model challengers—You can now challenge any of your production models, no matter where they are running, and regardless of the framework or language in which they were built.
Choose your own baseline (public beta)—Many organizations with forecasting models already in place are curious to compare the output of those models with predictions from DataRobot Automated Time Series (AutoTS). This comparison allows you to have confidence that DataRobot is forecasting as expected, and helps you understand if our models are more or less accurate than your existing ones.
Visual AI image augmentation—AutoML’s Visual AI capability now includes training-time image augmentation. When this feature is enabled, DataRobot will create training images from your dataset by randomly transforming existing images, thereby increasing the size of the training data through augmentation.
Enhanced prediction preparation—DataRobot’s self-service data preparation just got even more powerful in Release 7.0. Not only can you quickly and easily prepare your data for model training, you can also use our visual data prep capabilities to score new data after your models are built and use it for whatever purpose you choose.
Yes, of course there’s more!—Automatic bias and fairness testing is generally available in AutoML Release 7.0. This release also includes a new cross-class accuracy insight. Our DataRobot Data Prep contains enhanced Automated Process Flow (APF) monitoring, automatic date transformations, and a new elastic Spark-based infrastructure. AutoTS introduces monotonicity constraints and a new unsupervised anomaly over time model comparison feature. MLOps now includes support for connecting to GitHub Enterprise and Bitbucket Server. It also includes other valuable features to help you more effectively manage your production models.
We would very much like to walk you through all of the details of the release in a live environment, but until then, here are some highlights of the release. Make sure to tell us what you think of this release announcement, the demos, and the 7.0 features!
Public beta features
Every DataRobot release includes some features that have been tested by our engineering and quality teams, and are available for preview by a limited number of users. If you're a customer and are interested in giving some of these features a try, contact your CFDS or account executive for details on how you can participate.
Here are some public beta features you can check out now:
We’ve created a series of demo videos to help you understand the changes and guide you while using this release. Also, blogs are published periodically so please make sure to check our DataRobot.com Blog often. For the best experience, you can also subscribe to our blog and we’ll notify you about new posts.
Below are demo videos for many of the new and updated features.
Automated Machine Learning (AutoML)
Bias and Fairness Testing (copy and share link to this demo)
Enhanced Prediction Threshold UX (copy and share link to this demo)
Image Augmentation for Visual AI (copy and share link to this demo)
Automated Time Series (AutoTS)
Choose Your Own Baseline (PUBLIC BETA) (copy and share link to this demo)
Remote Model Challengers (PUBLIC BETA) (copy and share link to this demo)
PPS for Custom Models (PUBLIC BETA) (copy and share link to this demo)
Pulling and Testing Models from Bitbucket (PUBLIC BETA) (copy and share link to this demo)
Multiclass Model Monitoring (PUBLIC BETA) (copy and share link to this demo)
Integrations and Alliances
Tableau Analytics Extension (PUBLIC BETA) (copy and share link to this demo)
More information about the release
Make sure to watch the release 7.0 webinar which provides an overview of these new features and product demonstrations.
More information for DataRobot users: search in-app Platform Documentation for Release Center, and find the Version 7.0.0 release notes for AutoML or MLOps.
Tell us what you think
If this material is helpful, let us know. If you still have questions about the release, let us know. Other DataRobot Community members and our DataRobot experts will help fill in any blanks, and your feedback is critical to helping us get better. Click Comment and let us know.
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