[[ml-introduction]]
== Introduction

Machine learning in {xpack} automates the analysis of time-series data by
creating accurate baselines of normal behaviors in the data, and identifying
anomalous patterns in that data.

Driven by proprietary machine learning algorithms, anomalies related to temporal
deviations in values/counts/frequencies, statistical rarity, and unusual
behaviors for a member of a population are detected, scored and linked with
statistically significant influencers in the data.

Automated periodicity detection and quick adaptation to changing data ensure
that you don’t need to specify algorithms, models, or other data
science-related configurations in order to get the benefits of {ml}.
//image::graph-network.jpg["Graph network"]

=== Integration with the Elastic Stack

Machine learning is tightly integrated with the Elastic Stack.
Data is pulled from {es} for analysis and anomaly results are displayed in
{kb} dashboards.

//[float]
//== Where to Go Next

//<<ml-getting-started, Getting Started>> :: Enable machine learning and start
//discovering anomalies in your data.

//[float]
//== Have Comments, Questions, or Feedback?

//Head over to our {forum}[Graph Discussion Forum] to share your experience, questions, and
//suggestions.
