Google Webinar: Operationalizing ML Models with MLOps

  • Calendar
  • Jan 21 2020
    1:00 - 2:00 pm PST
  • Location
  • Online Webinar

Intro

MLOps require careful planning and professionals to help manage the production machine learning lifecycle. Similar to the DevOps, MLOps looks to increase automation and improve the quality of production ML while also focusing on business and regulatory requirements. MLOps applies to the entire ML lifecycle - from integrating with model generation (software development lifecycle, continuous integration/continuous delivery), orchestration, and deployment, to health, diagnostics, governance, and business metrics. In this webinar, we’ll discuss how to setup MLOps that will help support teams to manage AI projects. You’ll learn the primary functions of MLOps, and what tasks are suggested to accelerate your team's machine learning pipeline.

Agenda

Join us on January 21st at 1 PM PST to learn:

  • How to setup MLOps Process
  • Tools to manage ML lifecycle
  • Performance, diagnostics and governance of ML models
  • Building an automated CI/CD framework for model deployment

Presenters

Prabhu Palanisamy

Prabhu Palanisamy
President and Chief Strategy Officer, SpringML

Piyush Malik

Piyush Malik
VP Delivery, SpringML