On-demand webinar
Introduction to supervised machine learning in Elastic
Hosted by:
![Steve Dodson](https://static-www.elastic.co/v3/assets/bltefdd0b53724fa2ce/bltef1152819d83547b/5da7380eb4524f686fd7a1b3/headshot-steve-dodson-300x300.jpg)
Steve Dodson
Distinguished Engineer II
Elastic
![Tom Grabowski](https://static-www.elastic.co/v3/assets/bltefdd0b53724fa2ce/bltac40ead50bbd7800/5f4ec30199431928ffc0e68b/headshot-tom-grabowski-300x300.jpg)
Tom Grabowski
Principal Product Manager
Elastic
Overview
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:
- Training: Elastic Machine Learning for Cybersecurity
- Videos:
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