Today we continue our coverage of the AWS ML Summit joined by Chris Fregly, a principal developer advocate at AWS, and Antje Barth, a senior developer advocate at AWS.
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In our conversation with Chris and Antje, we explore their roles as community builders prior to, and since, joining AWS, as well as their recently released book Data Science on AWS. In the book, Chris and Antje demonstrate how to reduce cost and improve performance while successfully building and deploying data science projects.
We also discuss the release of their new Practical Data Science Specialization on Coursera, managing the complexity that comes with building real-world projects, and some of their favorite sessions from the recent ML Summit (which you can catch the videos for here).
Thanks to our sponsor!
Big thanks to our friends at Amazon Web Services for their continued support of the podcast, and their sponsorship of today’s show!If you missed the AWS Machine Learning Summit last week, you can still catch all the sessions on-demand at twimlai.com/awsmlsummit. There you’ll find more than 30 sessions and keynotes featuring some of the brightest minds in machine learning diving deep into the art, science, and impact of ML. You’ll hear from industry luminaries and leading experts on the latest science breakthroughs, get real-world examples of how ML is impacting business, and learn best practices in building ML to share with your team.
Connect with Chris!
Connect with Antje!
- Get the book Data Science on Amazon Web Services here!
- Join the Data Science on AWS Meetup here!
- AWS Machine Learning Summit Online | How Machine Learning is Done
- Practical Data Science Specialization
- Watch the ML Summit sessions here!