Introduction to supervised machine learning in Elastic

Introducing data frame analytics for supervised machine learning. Data frame analytics lets you build your own models using built-in regression, classification, and outlier detection jobs. Now with version 7.6 we will show you how to build a model and use it for real-time streaming data via the new inference ingest pipeline.

Highlights:

  • Building a regression model
  • Building a classification model
  • Using the Language Detection model
  • Integration between Elastic and Jupyter notebooks

Related Resources:

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  • Steve Dodson

    Machine Learning Tech Lead and Distinguished Engineer

    Elastic

    Tom Grabowski

    R&D

    Elastic

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