Testing ML systems
Practical AI
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Enhancing Collaboration for ML Deployment
This chapter explores the essential collaboration between data scientists and engineering teams in deploying machine learning models. It highlights the importance of role-specific testing and the implementation of a scoring rubric to identify weaknesses and improve practices. The discussion also addresses the significance of both manual and automated testing while emphasizing the often-overlooked area of infrastructure testing.
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