Using Small Datasets to Build Models in DataRobot

March 25, 2020
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· 1 min read

This post was originally part of the DataRobot Community. Visit now to browse discussions and ask questions about DataRobot, AI Cloud, data science, and more.

As the global coronavirus pandemic is causing major disruptions to communities and the economy, many existing data science models struggle to adapt to these shifts due to a shortage of available data.

Join our learning session “Using Small Datasets to Build Models” hosted by Dave Heinicke and Rajiv Shah (both Customer Facing Data Scientists) to learn more about:

  • Strategies to build a “cold start” model.
  • Checks to ensure you have meaningful, consistent signal from limited examples.
  • Diving deeper into model insights to verify meaningful model fit.

Hosts

  • Dave Heinicke (DataRobot, Customer Facing Data Scientist)
  • Rajiv Shah (DataRobot, Customer Facing Data Scientist)
  • Jack Jablonski (DataRobot, AI Success)
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About the author
Linda Haviland
Linda Haviland

Community Manager

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