
Shreya Shankar — Operationalizing Machine Learning
Gradient Dissent: Conversations on AI
The Four Stages of a Successful ML Deployment
Practitioners interviewed for the study identified four stages in their workflow around experimentation: evaluation and deployment monitoring and response, data collection, and versioning./nThe variables that govern success in each stage are the velocity of experimentation, the ability to validate early, and the stage of the product's development.
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