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[Demos + Webinar] Using open source *Delta Lake* and *dbt* in ML/data pipelines
April 18 @ 12:00 pm - 1:00 pm EDT
Talk #0: Introductions and Meetup Announcements By Chris Fregly and Antje Barth
Talk #1: Using Delta Lake with Amazon SageMaker
Speaker: Paul Hargis and Vedant Jain, Senior Solution Architects, AI and Machine Learning @ AWS
Talk #2: How to efficiently manage the Data Engineer | Data Scientist handoff with dbt, Redshift, and Sagemaker by Matt Winkler from *dbt Labs*
Description: dbt (data build tool) is an open source transformation framework which enables testing, documentation, and version control on top of data pipelines. In this talk, we’ll discuss how dbt can be used to manage feature engineering pipelines for Machine Learning, and the handoff points between dbt and models managed in AWS Sagemaker.
Speaker Bio: Hi, I’m Matt! I’m an ex- data scientist who chose to embrace the simplicity of SQL in managing and testing data pipelines with dbt. I’ve previously worked as a hands-on ML practitioner, and consulted with Fortune 500 clients to build and maintain ML Ops pipelines using (mostly) AWS Sagemaker. I live in the Denver area, and you can say hello on [dbt Slack](https://www.getdbt.com/community/join-the-community) or on [LinkedIn](https://www.linkedin.com/in/matt-winkler-4024263a/).
Zoom link: https://us02web.zoom.us/j/82308186562
O’Reilly Book: https://www.amazon.com/dp/1492079391/
GitHub Repo: https://github.com/data-science-on-aws/