DataRobot Blog

DataRobot offers end-to-end explainability to make sure models are transparent at all stages of their lifecycle. In this post, we’ll walk you through DataRobot’s Explainable AI features in both our AutoML and MLOps products and use them to evaluate a model both pre- and post-deployment. 

Whether with code or no code, clustering with multimodal is made easy. Learn more what is new in the DataRobot 7.3 release.

DataRobot’s team worked hard to take Visual AI to the next level. Learn more about several exciting new features.

No matter what language you bring to DataRobot, you can always expect to see the same great results. Learn more about the next generation of Text AI for the DataRobot AI Platform.

DataRobot is extending the power of the DataRobot AI Platform with a complete offering for code-first data science experts, DataRobot Core.

Evaluating bias is an important part of developing a model. Deploying a model that’s biased can lead to unfair outcomes for individuals and repercussions for organizations. DataRobot offers robust tools to test if your models are behaving in a biased manner and diagnose the root cause of biased behavior. However, this is only part of the story. Just because your model was bias-free at the time of training doesn’t mean biased behavior won’t emerge over time.

DataRobot Pathfinder Solution Accelerators help you quickly get started with the most popular AI use cases in just a few clicks.

Since I joined DataRobot nearly two years ago, I’ve been fortunate to spend much of my time meeting with and learning from our users and customers. Time and time again, we hear about the need for AI to support cross-functional teams and users. To provide the ability to integrate diverse data sources. To offer the flexibility to deploy AI solutions…

Our newly-launched DataRobot AI Platform turns the possibilities of AI into tangible realities. How? By being built specifically for the demands, challenges, and opportunities of AI today.