rszper commented on code in PR #22250:
URL: https://github.com/apache/beam/pull/22250#discussion_r920496197


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website/www/site/content/en/documentation/sdks/python-machine-learning.md:
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+---
+type: languages
+title: "Apache Beam Python Machine Learning"
+---
+<!--
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+-->
+
+# Machine Learning
+
+You can use Apache Beam with the RunInference API to use machine learning (ML) 
models to do local and remote inference with batch and streaming pipelines. 
Starting with Apache Beam 2.40.0, PyTorch and Scikit-learn frameworks are 
supported. You can create multiple types of transforms using the RunInference 
API: the API takes multiple types of setup parameters from model handlers, and 
the parameter type determines the model implementation.
+
+## Why use the RunInference API?
+
+RunInference leverages existing Apache Beam concepts, such as the the 
`BatchElements` transform and the `Shared` class, and it allows you to build 
multi-model pipelines. In addition, the RunInference API has built in 
capabilities for dealing with [keyed 
values](#use-the-prediction-results-object).

Review Comment:
   I'll remove it



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