Wednesday Apr 25
15:15 –
16:00
Room 205-206
Production Model Deployment
Slides:
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Have you built a model you’re confident in? Great! Now, you need to put it into production. Generally, this means reliably transmitting the output of a model to another system, but people can mean a lot of things when they say deployment: data, API, or code artifact deployments. First, we will discuss how these deployment types fit into model development workflows and integrate with outside systems. Then we will move on to the fun, gnarly stuff -- challenges in deployment and strategies from across the industry for managing these issues.
machine learning (ML)
continuous delivery
production
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Exploring StackOverflow DataEvelina GabasovaWednesday Apr 25, 11:15
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Developing a ML modelKevin TsaiWednesday Apr 25, 13:00
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Production Model DeploymentJuliet HouglandWednesday Apr 25, 15:15
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Life and Death Decisions: Testing Data SciencePhil WinderWednesday Apr 25, 14:00
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Relating to Machine LearningStefan Veis PennerupWednesday Apr 25, 10:15
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Delivering AI on Code: Live Demo of source{d}Francesc CampoyWednesday Apr 25, 16:15