Written by poppy

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 workshop, you will go through that workflow using Amazon SageMaker by building, training and optimizing a model to predict if a customer will enroll for a term deposit when using direct marketing. Finally, you will deploy the model in production, where you will be able to start generating predictions and measure the quality of those predictions.

This will be a fully interactive workshop, with hands-on learning outcomes. You will walk away with an understanding of how you can remove the complexity and barriers that typically slow down developers using ML.

Laptops are required for this session.

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