CALL FOR PAPERS

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

Bespoke

845 Market St Suite 450

San Francisco, CA 94103

May 6th, 2020

For questions and to inquire about sponsorship, let's talk:

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