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#MLOpsNYC19
CALL FOR PAPERS - CLOSED
Have something interesting to say about MLOps? We're waiting for your proposal!
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Suggested Topics:
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KubeFlow standardization
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MLSpec
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MLRun
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AI use-cases in business applications
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Machine learning deployment and operation challenges
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Machine learning model training at scale
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Machine learning pipeline automation
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Serverless in machine learning
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Model deployment and monitoring in production
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Implementing AI in real-time and interactive applications
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Model versioning and reproducibility
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Data and feature vector access in production
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Security challenges in production
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Using GPUs to accelerate training and inferencing
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MLFlow
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Working in heterogeneous environments (multi-cloud, edge, on-premises)
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Machine learning best practices
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This CfP is now closed.
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