35 lines
1.2 KiB
Plaintext
35 lines
1.2 KiB
Plaintext
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[[ml-introduction]]
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== Introduction
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Machine learning in {xpack} automates the analysis of time-series data by
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creating accurate baselines of normal behaviors in the data, and identifying
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anomalous patterns in that data.
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Driven by proprietary machine learning algorithms, anomalies related to temporal
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deviations in values/counts/frequencies, statistical rarity, and unusual
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behaviors for a member of a population are detected, scored and linked with
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statistically significant influencers in the data.
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Automated periodicity detection and quick adaptation to changing data ensure
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that you don’t need to specify algorithms, models, or other data
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science-related configurations in order to get the benefits of {ml}.
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//image::graph-network.jpg["Graph network"]
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=== Integration with the Elastic Stack
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Machine learning is tightly integrated with the Elastic Stack.
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Data is pulled from {es} for analysis and anomaly results are displayed in
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{kb} dashboards.
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//[float]
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//== Where to Go Next
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//<<ml-getting-started, Getting Started>> :: Enable machine learning and start
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//discovering anomalies in your data.
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//[float]
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//== Have Comments, Questions, or Feedback?
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//Head over to our {forum}[Graph Discussion Forum] to share your experience, questions, and
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//suggestions.
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