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MODEL VERSIONING: WHY, WHEN, AND HOW
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Talks & recordings
2 connected sessions
Model Monitoring in Production
Real mission critical AI systems require advanced monitoring and model observability that enables continuous and reliable delivery of ML models into production. This demo-based talk covers data drift detection, model degradation, and the full cycle of ML in production with Kubeflow pipelines.
Model Versioning: Why, When, and How
Models are the new code. In the wild-west of data science and ML tools, versioning, management, and deployment of models are massive hurdles. Drawing on experience with ModelDB and Verta, this talk presents best practices and tools for model versioning—a Git for ML models—enabling rapid deployment and high quality of deployed ML models.
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Connections
6 relationships
part_of · incomingSF Scala: Manasi Vartak Interviewtalk ↗part_of · incomingSF Scala: Manasi Vartak Interviewtalk ↗photos fromBay Area AI @D2iQ Inc. 20191105photo ↗presented at · incomingModel Monitoring in Productiontalk ↗presented at · incomingModel Versioning: Why, When, and Howtalk ↗part ofBay Area AIproject ↗