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Fix links in ML commons index 

Signed-off-by: Naarcha-AWS <naarcha@amazon.com>
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Naarcha-AWS 2022-03-23 08:46:40 -05:00
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_ml-commons-plugin/index.md
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@ -10,7 +10,7 @@ has_toc: false
ML Commons for OpenSearch eases the development of machine learning features by providing a set of common machine learning (ML) algorithms through transport and REST API calls. Those calls choose the right nodes and resources for each ML request and monitors ML tasks to ensure uptime. This allows you to leverage existing open-source ML algorithms and reduce the effort required to develop new ML features.
Interaction with the ML commons plugin occurs through either the [REST API]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api) or [AD]({{site.url}}{{site.baseurl}}/ppl/commands#ad) and [kmeans]({{site.url}}{{site.baseurl}}/observability-plugin/ppl/commands#kmeans) PPL commands.
Interaction with the ML commons plugin occurs through either the [REST API]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api) or [AD]({{site.url}}{{site.baseurl}}/observability-plugin/ppl/commands#ad) and [kmeans]({{site.url}}{{site.baseurl}}/observability-plugin/ppl/commands#kmeans) PPL commands.
Models [trained]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api#train) through the ML Commons plugin support model-based algorithms such as kmeans. After you've trained a model enough so that it meets your precision requirements, you can apply the model to [predict]({{site.url}}{{site.baseurl}}/ml-commons-plugin/api#predict) new data safely.