AnandInguva opened a new issue, #26640:
URL: https://github.com/apache/beam/issues/26640

   ### What would you like to happen?
   
   We aim to create an easy-to-use `PTransform` in Apache Beam, called 
MLTransform, for carrying out common machine learning transforms on large 
datasets. MLTransform is designed to be framework-agnostic, and its primary 
goal is to provide an intuitive interface for users to perform various data 
processing transformations without writing complex code or dealing with 
underlying libraries. The first framework that we will make use of is 
TensorFlow Transform (TFT) which has many production hardened transformations 
already written using the Apache Beam primitives. 
   
   Design doc: 
https://docs.google.com/document/d/1rQkSm_8tseLqDQaLohtlCGqt5pvMaP0XIpPi5UD0LCQ/edit#
   dev list discussion: 
https://lists.apache.org/thread/d4thp7xs1y0jm5m9v5xzshln9fwvsm7s
   
   ### Issue Priority
   
   Priority: 2 (default / most feature requests should be filed as P2)
   
   ### Issue Components
   
   - [X] Component: Python SDK
   - [ ] Component: Java SDK
   - [ ] Component: Go SDK
   - [ ] Component: Typescript SDK
   - [ ] Component: IO connector
   - [ ] Component: Beam examples
   - [ ] Component: Beam playground
   - [ ] Component: Beam katas
   - [ ] Component: Website
   - [ ] Component: Spark Runner
   - [ ] Component: Flink Runner
   - [ ] Component: Samza Runner
   - [ ] Component: Twister2 Runner
   - [ ] Component: Hazelcast Jet Runner
   - [ ] Component: Google Cloud Dataflow Runner


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