DataRobot Blog

Using new and relevant features of the DataRobot AI Cloud Platform, the DataRobot team will highlight four applications of Trusted AI for homeland security.

In this post, we will dive deeper into managing model risk, and look at opportunities at how automation provided through DataRobot brings about efficiencies in the development and implementation of models.

We’re excited to announce our partnership with Labelbox, the leading provider of unstructured data labeling capabilities. Labelbox’s technology reduces the time required to label complex datasets by 5-10 times, allowing a small team to no longer need to iterate for months to deliver accurate training data for high model performance.

To make laser-sharp predictions, McLaren’s Formula 1 drivers and team members use DataRobot automated time series capabilities to forecast air and track temperatures.

The stakes in managing model risk are at an all-time high, but luckily automated machine learning provides an effective way to reduce these risks. Learn more.

Part 2 in a series on the emerging practice of "green AI." In this blog, the focus is on actionable ways AI practitioners can build their models to minimize the cost of Red AI.

Find out how to approach machine learning projects in a sustainable and cost-efficient manner by reassessing the efficiency metrics applies to models.

Another year at HIMSS has come and gone and DataRobot remains as energized as ever! This year was a big moment for the DataRobot team. We debuted our growing healthcare organization, offered a preview of the AI Cloud DataRobot 8.0 release, and had hundreds of conversations surrounding the impact of AI and the substantial support for the healthcare industry.