Have something interesting to say about MLOps? We're waiting for your proposal! 

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Suggested Topics:

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• Open source technologies for MLOps

• KubeFlow standardization 

• MLRun

• MLFlow

• Online and offline feature stores

• Experiment and data tracking

• Reinforced machine learning

• AI use-cases in business applications

• Machine learning deployment and operation challenges

• Machine learning model training at scale

• Machine learning pipeline automation

• Serverless in machine learning pipelines

• Model deployment and monitoring in production

• Implementing AI in real-time and interactive applications

• Model versioning and reproducibility

• Data and feature vector access in production

• Security challenges in production

• Using GPUs to accelerate training and inferencing

• Working in heterogeneous environments (multi-cloud, edge, on-premises)

• Distributed machine learning

• Spark and big data over Kubernetes 

• Natural language processing at scale

• Cost optimization of machine learning pipelines

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CFP deadline is March 16 2020

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