[role="xpack"]
[[ml-df-trained-models-apis]]
= {ml-cap} trained model APIs

.New API reference
[sidebar]
--
For the most up-to-date API details, refer to {api-es}/group/endpoint-ml-trained-model[{ml-cap} trained model APIs].
--

You can use the following APIs to perform model management operations:

* <<clear-trained-model-deployment-cache>>
* <<put-trained-models>>
* <<put-trained-model-definition-part>>
* <<put-trained-model-vocabulary>>
* <<put-trained-models-aliases>>
* <<delete-trained-models>>
* <<delete-trained-models-aliases>>
* <<get-trained-models>>
* <<get-trained-models-stats>>
* <<infer-trained-model>>
* <<start-trained-model-deployment>>
* <<stop-trained-model-deployment>>
* <<update-trained-model-deployment>>

You can deploy a trained model to make predictions in an ingest pipeline or in
an aggregation. Refer to the following documentation to learn more:

* <<search-aggregations-pipeline-inference-bucket-aggregation,{infer-cap} bucket aggregation>>
* <<inference-processor,{infer-cap} processor>>