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: