Learning Amazon SageMaker

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Created by: Martin Kemka

Produced in 2019

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Course Description

SageMaker is Amazon's solution for developers who want to deploy predictive machine learning models into a production environment. Programming is done in Python and the results can easily be integrated into cloud-based applications. These lessons review the entire Amazon SageMaker workflow: analysis, build, and final deployment. Instructor Martin Kemka introduces the benefits of Amazon SageMaker and reviews its browser-based interface and toolset. In the second chapter, he shows how to import, investigate, visualize, and summarize your data. The next stage is to use a clean data sample to train a machine learning model to fulfill a basic task. Finally, Martin shows how the model is deployed. Almost every chapter concludes with a challenge that allows you to practice your new SageMaker skills.

Intermediate Level

Time: 1h 11m

Instructor Details

Martin Kemka

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Martin Kemka is the founder of Northraine, a machine learning production house.

Over the past decade, Martin has led, designed, and created innovative predictive analytics solutions for a number of corporations, including GE, Equifax, D&B, the World Bank, and Xerox. He has also contributed pro bono algorithms and research to global human rights and social institutions. Through university partnerships, Northraine has grown into a consultancy that spends 40% of time on research and 60% of time designing algorithms to - recondition the human condition.- Find out more at https://www.northraine.com/..