We present a rubric as a set of 28 actionable tests, and offer a scoring system to measure how ready for production a given machine learning system is This rubric is intended to cover a range from a team just starting out with machine learning up through tests that even a well-established team may find difficult
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[PDF] Monitoring and explainability of models in production - Seldon
The ml test score: A rubric for ml production readiness and technical debt reduction In Proceedings of IEEE Big Data, 2017 Bridge, P , Fielding, A , Rowntree, P
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The ML Test Score: A Rubric for · ML Production Readiness and Technical Debt Reduction Implement and automate tests for all parts of the ML pipeline
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For this purpose, we conducted a case study to analyze ML models These models will go into production and then integrated to the software system owned by
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30 jui 2020 · 12 3 2 Testing and Validating Machine Learning Systems [35] E Breck, S Cai , E Nielsen, M Salib, and D Sculley, “The ml test score: A rubric for ml production readiness and technical debt reduction,” Big Data, pp
[PDF] Whats your ML Test Score? A rubric for ML production systems
Using machine learning in real-world production systems is complicated by a host of issues not We present an ML Test Score rubric based on a set of actionable tests to help quantify useful to gauge a team's readiness to field a real-world ML system Machine learning: The high interest credit card of technical debt
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data that drive production machine learning pipelines Our The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction
[PDF] Data Validation for Machine Learning - MLSys
data validation in the context of ML: early detection of errors, model-quality wins from using better data, savings essary to reduce technical debt and ensure product readiness The ml test score: A rubric for ml production readiness
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