November 27, 2019

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Data science in the cloud

Data science in the cloud

In this talk Alex will discuss lessons learned from AWS SageMaker, an integrated framework for handling all stages of analysis. AWS uses open source components such as Jupyter, Docker containers, Python and well established deep learning frameworks such as Apache MxNet and TensorFlow for an easy to learn workflow.

Talk Title Data science in the cloud
Speakers Alex Smola (Amazon)
Conference Strata Data Conference
Conf Tag Big Data Expo
Location San Jose, California
Date March 6-8, 2018
URL Talk Page
Slides
Video Talk Video

Statistical data analysis involves multiple stages of data preprocessing, analysis, modeling, training, parameter optimization, testing and serving. In this talk, Alex will discuss lessons learned from AWS SageMaker, an integrated framework for handling all stages of analysis. AWS uses open source components such as Jupyter, Docker containers, Python and well established deep learning frameworks such as Apache MxNet and TensorFlow for an easy to learn workflow. At the same time, flexibility to integrate third party code and management is vital for real world deployment.

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