Developer Webinar Series | Webinar #3

Deployment of Machine Learning Pipeline with SageMaker and Step Functions (AWS)

Now Available On Demand

Machine Learning is becoming a larger part of companies' core business so automating the build and deployment is increasingly necessary. Listen to our webcast to find out more.

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As machine learning (ML) becomes a larger part of companies’ core business, there is a greater emphasis on reducing the time from model creation to deployment. Automating the build and deployment of machine learning models is becoming common ask for many organisations worldwide.  

AWS Step Functions allows you to coordinate several AWS services into a serverless workflow. You can design and run workflows in which the output of one step acts as the input to the next step, and embed error handling into the workflow. 

Amazon SageMaker is a fully managed service that provides developers and data scientists with the tools to build, train, and deploy different types of ML models. 

This webinar, first broadcast on August 13, we will demonstrate how to create Machine Learning pipeline that includes training and deployment of Machine Learning model using Python code and make this process repeatable.  

Why should you attend?
  • Learn how to use AWS Step Functions Data Science Python SDK to define Machine Learning pipeline
  • Learn how to deploy Machine Learning pipeline
  • Learn how to automate SageMaker jobs with the code
Deployment of Machine Learning Pipeline with Sage Maker and Step Functions (AWS)
Now Available On Demand
Meet our speakers
Ievgen Goichuk

Senior Software Engineer
Refinitiv Labs
Laura Sartenaer
Strategy and Partnerships, EMEA 
Refinitiv Labs
Ievgen is a technology enthusiast from the past 20 years and is a software engineer with Refinitiv Labs team in London. He is a Computer Science graduate and has been designing and delivering software solutions for numerous clients in Finance, E-Commerce, and Media for over two decades. His expertise includes real-time distributed systems, Cloud engineering, Machine Learning engineering, DLT. 
Laura manages Strategy and Partnerships, EMEA at Refinitiv Labs (formerly Thomson Reuters Financial & Risk). In this role, she assesses market and emerging technology trends to help inform the Labs strategy, as well as initiates and develops key industry relationships with customers, big tech firms, start-ups, governments, trade bodies, universities and research institutes. She is also a Member of the World Economic Forum’s Working Group for AI in Financial Services. Prior to this, Laura spent 2.5 years in the Corporate Strategy and M&A team, where she led the development of the Financial Crime Risk Management strategy and Artificial Intelligence strategy. Before joining Refinitiv in September 2016, Laura spent two years as a European Equities Research Analyst at Third Bridge, a primary research firm in London. 
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Refinitiv, is one of the world’s largest providers of financial markets data and infrastructure. Serving more than 40,000 institutions in approximately 190 countries, we provide information, insights, and technology that drive innovation and performance in global markets. Our 160-year Reuters heritage of integrity enables customers to make critical decisions with confidence, while our unique open platform, best-in-class data, and cutting-edge technology bring greater opportunity to our customers. By advancing our customers, we drive progress for the entire financial community.

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