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Machine Learning Operations (MLOps)

Machine learning operations is the machine-learning equivalent of DevOps: it solves the problems of implementing machine-learning in production, notably around the technology infrastructure and tooling necessary to deploy machine-learning algorithms and data pipelines reliably and scalably, so as not to destabilize other parts of the stack.

Machine Learning Server

Machine learning faces challenges to scaling at the four main stages of its workflow:

  • ETL (Data pipelines)
  • Algorithm training
  • Inference
  • Monitoring, Management and Updates

The Skymind Intelligence Layer (SKIL) is a machine learning server that solves the problem of serving machine-learning models at scale during the inference phase.

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