AWS SageMaker

AWS SageMaker is a fully managed machine learning service that enables developers to quickly and easily build, train, and deploy machine learning models at scale. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high-quality models.

Amazon SageMaker is a fully-managed machine learning service that makes it easy for data scientists and developers to quickly and easily build, train, and deploy models into a production-ready hosted environment. It provides an integrated Jupyter notebook instance for convenient access to data sources for exploration and analysis, eliminating the need to manage servers. Additionally, it offers optimized common machine learning algorithms that are designed to function efficiently with large data sets in distributed environments. SageMaker also allows users to bring their own algorithms and frameworks and offers flexible distributed training that can be adapted to individual workflows. Models can be quickly deployed into a secure and scalable environment using the SageMaker Studio or the SageMaker console.

AWS Amazon SageMaker

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AWS SageMaker Hackathon projects

Solutions built with AWS SageMaker that have been created during our hackathons by the members of our community