Tech It Easy: MLOps with Amazon SageMaker Pipelines

Tech It Easy: MLOps with Amazon SageMaker Pipelines
Event Info
April 6, 2022
4:00 PM - 4:30 PM Europe/London


The value of ML-enabled applications is rising in the world of business and this has led to a tremendous increase in ML projects. Quite shockingly, despite this rise and the increased investment we’re currently seeing only 20% of data science ML projects actually make it to production.

In this webinar we will not only reinforce the value in which MLOps can bring to your business, but as early adopters of and specialists in the field we will show you examples of how our clients have found success; and more specifically how we’ve helped a media organisation to modernise their AWS machine learning platform.

We have designed this webinar to help CDO’s, Heads of Data, Data Science and Analytics in different industries to understand why their businesses need to develop machine learning capabilities’ and incorporate AWS technologies into their current ecosystem.

Why Attend?

Tech It Easy is back and following last year’s 6-part series we have an exciting new schedule of webinars and events lined up for you this year. We will continue to delve into the use of AWS technologies and the ways in which they can steer your business to success.

Part #1 in our series is a webinar focusing on MLOps with Amazon SageMaker Pipelines. This webinar will provide attendees with:

  • A clear understanding of MLOps and its core concepts
  • An Industry success story - MLOps at a media organisation
  • Best practices from industry experts
  • A walkthrough 'show-me-how' session
  • Opportunity to ask questions

Amazon SageMaker has been helping businesses build, train & deploy machine learning models at scale and by the end of this webinar you will learn how to use SageMaker Pipelines to orchestrate a machine learning pipeline and deploy models


  • Introduction
  • AWS: Machine Learning
  • MLOps Definition and Core Concepts
  • Industry Success Story
  • Show Me How - Our Practical Demo!
  • Q&A


Pavi Singh - Senior Data Scientist at Data Reply

Richie Bird - Data Scientist at Data Reply

Mayur Udernani - AI and Machine Learning Leader at AWS

Nil Patel - Global Data & Analytics Director at Indicia Worldwide

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