DataRobot Blog

You need to know where your deployed models are, what they do, the data they use, the results they produce, and who relies upon their results. That requires a good model governance framework.

At the confluence of cloud computing, geospatial data analytics, and machine learning we are able to unlock new patterns and meaning within geospatial data structures.

In this post, we will dive deeper into strategies an organization may take to monitor their production ML systems, and make certain that the systems are working for their intended purposes in a deployed environment.

Despite the great outcomes the use of AI in Real Estate promises, there are still some hurdles to overcome. Read more.

In this blog post, the DataRobot team will show how the DataRobot AI 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 Platform to aid in both proactive and reactive disaster response using the wide range of features available on the platform.

The DataRobot AI 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.