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MLOps: 5 Steps to Operationalize Data Science

Ensure that your data science project delivers business value

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How can you ensure that your AI/ML projects will succeed? A framework and architecture to support model-building, deployment, and monitoring can help.

Join us for “MLOps: 5 Steps to Operationalize Data Science” to learn about a new practice to help your data scientists, data engineers, and IT professionals work together to automate and productize algorithms. You will learn:

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Informatica will use data provided here in accordance with our privacy policy.

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Please complete the form below to watch this webinar

All fields are required.

Informatica will use data provided here in accordance with our privacy policy.

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

  • What MLOps is
  • Its key role in generating business value from data science projects
  • The five steps of MLOps .

Speakers

  • Sumeet Agrawal, Product Management, Informatica

  • Anant Mittal, Research & Development, Informatica

  • Vamshi Sriperumbudur, Portfolio Marketing, Informatica