Transcription of Practitioners guide to MLOps: A framework for continuous ...
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Practitioners guide to MLOps: A framework for continuous ...
Practitioners guide to MLOps: A framework for continuous delivery and automation of machine paperMay 2021 Authors: Khalid Salama, Jarek Kazmierczak, Donna SchutTable of ContentsExecutive summary 3 Overview of MLOps lifecycle and core capabilities 4 Deep dive of MLOps processes 15 Putting it all together 34 Additional resources
Deloitte identified lack of talent and integration issues as factors that can stall or derail AI initiatives.3 Algorithmia’s survey highlighted that challenges in deployment, scaling, and versioning efforts still hinder teams from getting value from their investments in ML.
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