DataRobot Blog

In this blog post, the DataRobot team will show how the DataRobot AI Cloud Platform can build models to predict if an employee will depart an organization in the next six months.

In this post, we will dive deeper into how members from both the first and second line of defense within a financial institution can adapt their model validation strategies in the context of modern ML methods.

In this blog post we will demonstrate the potential of the DataRobot AI Cloud Platform to aid in both proactive and reactive disaster response using the wide range of features available on the platform.

DataRobot’s AI Cloud Platform can enable effective and secure border transportation by predicting activity at crossing points to support better decisions about staffing levels.

This blog post will demonstrate how the DataRobot team applied DataRobot’s Visual AI and AutoML capabilities to rapidly build models capable of detecting firearms in bags.

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.