Machine Learning Operations (MLOps): Deploy at Scale

Alex Cattle

on 10 September 2019

What do successful deployments have in common?

Artificial Intelligence and Machine Learning adoption in the enterprise is exploding from Silicon Valley to Wall Street with diverse use cases ranging from the analysis of customer behaviour and purchase cycles to diagnosing medical conditions.

Following on from our webinar ‘Getting started with AI’, this webinar will dive into what success looks like when deploying machine learning models, including training, at scale. The key topics are:

  • Automatic Workflow Orchestration
  • ML Pipeline development
  • Kubernetes / Kubeflow Integration
  • On-device Machine Learning, Edge Inference and Model Federation
  • On-prem to cloud, on-demand extensibility
  • Scale-out model serving and inference

This webinar will detail recent advancements in these areas alongside providing actionable insights for viewers to apply to their AI/ML efforts!

Watch the webinar

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What is Kubernetes?

Kubernetes, or K8s for short, is an open source platform pioneered by Google, which started as a simple container orchestration tool but has grown into a platform for deploying, monitoring and managing apps and services across clouds.

Learn more about Kubernetes ›

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