April 27 | 11:00 AM - 12:00 PM PT
Level 200 | Solutions Best Practices
Customers are looking to use machine learning (ML) to perform predictive analytics within Tableau, a popular business intelligence (BI) tool. But building a custom integration to access ML models that are deployed on Amazon SageMaker from Tableau can take time and resources. The new Quick Start solution from AWS and Tableau makes it easy for data analysts to use ML models deployed on Amazon SageMaker directly in their Tableau dashboards, enabling ML-driven predictive analytics without writing any custom integration code. In this tech talk, learn how the solution works and how to deploy it. We'll also do an end-to-end demo and discuss some of the common use cases for the integration.
- Understand how the Amazon SageMaker for Tableau integration works
- Learn how to use Amazon SageMaker Autopilot to train a machine learning model and deploy it
- Learn how to deploy the integration, and how to make ML-driven predictions in Tableau dashboards
Who Should Attend?
Data and Business Analysts, BI Engineers, Data Scientists, IT and Devops Engineers
- Kosti Vasilakakis, Sr. Business Development Manager, AWS
- Nathan Mannheimer, Director of Data Science and ML Products, Tableau
- Holt Calder, Data Architect, Interworks
Intro body copy here about 2018 re:Invent launches.
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Service How To
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