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[DOCS] Removes ML content from index.asciidoc files (#1262)
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[role="xpack"] | ||
[[xpack-ml]] | ||
= {anomaly-detect-cap} | ||
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[partintro] | ||
-- | ||
Use {anomaly-detect} to analyze time series data by creating accurate baselines | ||
of normal behavior and identifying anomalous patterns in your dataset. Data is | ||
pulled from {es} for analysis and anomaly results are displayed in {kib} | ||
dashboards. | ||
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* <<ml-overview>> | ||
* <<ml-concepts>> | ||
* <<ml-configuration>> | ||
//* <<ml-getting-started>> | ||
* <<ml-api-quickref>> | ||
* <<ootb-ml-jobs>> | ||
* <<ml-functions>> | ||
* <<anomaly-examples>> | ||
* <<ml-limitations>> | ||
//* <<ml-troubleshooting>> | ||
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-- |
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[role="xpack"] | ||
[[ml-dfanalytics]] | ||
= {dfanalytics-cap} | ||
:stem: | ||
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[partintro] | ||
-- | ||
IMPORTANT: Using {dfanalytics} requires source data to be structured as a two | ||
dimensional "tabular" data structure, in other words a {dataframe}. | ||
{ref}/transforms.html[{transforms-cap}] enable you to create | ||
{dataframes} which can be used as the source for {dfanalytics}. | ||
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experimental[] | ||
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{dfanalytics-cap} enable you to perform different analyses of your data and | ||
annotate it with the results. | ||
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* <<ml-dfa-overview>> | ||
* <<ml-dfa-concepts>> | ||
* <<ml-dfanalytics-apis>> | ||
* <<dfanalytics-examples>> | ||
* <<ml-dfa-limitations>> | ||
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-- |