Uber open-sources internal machine learning platform Michelangelo
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Uber has open-sourced its internal machine learning platform Michelangelo. Uber says the platform supports more than 400 active ML projects, more than 20,000 model training jobs per month, more than 5,000 production models, and a real-time prediction peak of more than 45 million per second. The open-source version provides capabilities such as distributed training, one-click deployment, and canary releases; feature management, evaluation, and monitoring are labeled "coming soon." Uber also provides a Python API example based on uniflow and Ray. All the above scale figures are Uber's own statements.
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- Hacker News AIMichelangelo AI
Michelangelo AI is now open source, with the material citing Uber-scale usage of 400+ active ML projects, 20K+ model training jobs per month, 5K+ models in production, and 45M+ real-time predictions per second at peak. It offers feature management, model training, evaluation, deployment, and monitoring, with feature management, evaluation, and monitoring marked coming soon. A Python API example shows distributed XGBoost training with Ray and an end-to-end training workflow.
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