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

Suggested Topics:

  • 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

CFP deadline is March 16 2020

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