Building machine learning models is a creative process that requires deep thinking and expertise. But there's a lot of drudgery required to find and prep the data to train your ML model, not to mention getting that model into production or re-training it later. Whether you're using H2O.ai, Spark MLlib or any other machine learning framework, building your ML model is just one step in the longer process of getting machine learning into production.

Watch this Infoworks/Databricks joint webinar for discussion and demo on how to:

  • Find and prep the data to train your ML model in hours instead of days
  • Easily integrate the data with ML environments such as Databricks Notebooks
  • Get an ML model into production more quickly
  • Re-train the model with a push of the button

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