Michelangelo is the machine learning platform of Uber. It enables users across the company to build, deploy and operate machine learning solutions at their scale. It is designed to cover the whole machine learning workflow, manage data, train, evaluate and deploy models, make predictions and monitor predictions.
It is the internal ML-as-a-service platform that democratizes machine learning and makes scaling AI to meet the needs of business as easy as requesting a ride. It is created to be the system that addresses scalable model training and dispatch to production serving vessels.
The Uber Engineering team started the development of Michelangelo in mid 2015. It was built with a mix of open source systems and components made in-house. The primary open sourced components used are HDFS, Spark, Samza, Cassandra, MLLib, XGBoost, and TensorFlow.
UberEats, a food delivery application uses Michelangelo as its machine learning platform.
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Jeremy Hermann and Mike Del Balso
Meet Michelangelo: Uber’s Machine Learning Platform
Meet Michelangelo, Uber’s Machine Learning SaaS Platform
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