Traditional machine learning (ML) development is a complex, expensive, and iterative process made even more difficult because of the lack of integrated tools connecting the entire ML workflow. Users often need to stitch together tools and workflows, which is time-consuming and error-prone. Amazon SageMaker solves this challenge by providing all of the components used for machine learning in a single toolset so models get to production faster with much less effort and at lower cost. In this session, you learn about all of the different services within SageMaker that allow you to build, train, optimize and deploy a model ready for production. You will walk away with an understanding of how you can remove the complexity and barriers that typically slow down developers using machine learning.