DataRobot Location AI for AutoML

Community Team
Community Team
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(Part of a model building learning session series.)

In version 6.1, DataRobot released Location AI for AutoML which enables geospatial capabilities in machine learning models. Geospatial analysis is critical to a wide variety of industries and use cases, and the combination of machine learning and geospatial analysis is emerging as a valuable tool for improving modeling in these domains.

The new Location AI tools provide DataRobot users with tools for geospatial file ingest, geospatial visualizations, spatial modeling, and geospatial model insights.

In this learning session, we will introduce DataRobot's Location AI capabilities and survey the industries and use cases that stand to benefit immediately from the emerging use of geospatial analysis in their machine learning workflows. We will also cover some data preparation and modeling strategies; these will help you get up and running with Location AI to make sure you get the most out of your geospatial data.

Hosts

  • Kevin Stofan (DataRobot, Data Scientist)
  • Rajiv Shah (DataRobot, Customer Facing Data Scientist)
  • Jack Jablonski (DataRobot, AI Success Manager)

More Information

  • If you’re a licensed DataRobot customer, search the in-app Platform Documentation for Location AI.

Let us know what you think!

Have questions not answered during the learning session? What to continue your conversation with Kevin, Rajiv, and Jack? You can send email to learning_sessions@datarobot.com or Post Your Comment here. We're looking forward to hearing from you!

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