Predicting Customer Behavior with Amazon SageMaker Studio - Seguridad Mania.com - España y América Latina

The power of machine learning allows us to produce actionable insights with our data and streamline decision making, but it can be challenging to manage ML development workflow due to a lack of advanced ML tooling. Learn how you can leverage Amazon SageMaker Studio, a fully integrated development environment for ML in AWS, to easily and quickly build machine learning models under a convenient and intuitive single pane of glass. We’ll explore the Amazon SageMaker Studio service and discuss how the integrated visual interface manages workflow in order to build, train, and deploy machine learning models at scale. What we’ll cover: - An introduction to Amazon SageMaker Studio - Core features such as SageMaker Studio Notebooks, Autopilot and Experiments - How to enable and create your own Amazon SageMaker experiments - How to engineer features, tune models and obtain data for analysis