Effective Domain-Driven Design for Machine Learning Products

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Effective Domain-Driven Design for Machine Learning Products

Discovering and Prioritizing AI/ML Use Cases with DDD - Larysa Visengeriyeva

By DataTalks.Club

When and where

Date and time

Wednesday, April 19 · 7:30 - 9am PDT



About this event

  • 1 hour 30 minutes
  • Mobile eTicket

In this hands-on workshop, we’ll learn how to find and verify AI/ML use cases and get the right tools and procedures for product finalization. We use effective DDD methodology (no previous DDD knowledge necessary)

In this workshop, we’ll cover the following:

  • Find out which problems and use cases are suitable for ML
  • Define and prioritize problems and opportunities for ML in business areas and projects
  • Learn how to use the Data Landscape Canvas
  • Learn the knowledge crunching method of event storming used in DDD in a case study and apply it yourself
  • Learn how to use the Machine Learning Canvas to structure ML projects

By the end of this workshop, you’ll be able to apply Domain-Driven Design methodology to effectively structure machine learning projects.

About the speaker:

Larysa is a senior consultant with INNOQ in Berlin. She received her doctorate in Augmented Data Quality Management at TU Berlin. At INNOQ she is working on the operationalization of Machine Learning (MLOps). She‘s the author of ml-ops.org.

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