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MLFlow Platform

Princeton University_070820A
(Photo: Princeton University, Office of Communications)



- Overview

MLflow is an open source platform for managing the end-to-end machine learning (ML) lifecycle. It tackles four primary functions:  

  • Tracking experiments to record and compare parameters and results (MLflow Tracking). 
  • Packaging ML code in a reusable, reproducible form in order to share with other data scientists or transfer to production (MLflow Projects). 
  • Managing and deploying models from a variety of ML libraries to a variety of model serving and inference platforms (MLflow Models). 
  • Providing a central model store to collaboratively manage the full lifecycle of an MLflow Model, including model versioning, stage transitions, and annotations (MLflow Model Registry).

MLflow is library-agnostic. You can use it with any machine learning library, and in any programming language, since all functions are accessible through a REST API and CLI. For convenience, the project also includes a Python API, R API, and Java API.



[More to come ...]

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