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.
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