Build ML models at scale with Amazon SageMaker Studio Notebooks | Amazon Web Services

Опубликовано 7 сентября 2022, 20:47

Amazon SageMaker Studio Notebooks are quick start, collaborative notebooks that integrate with purpose-built ML tools in SageMaker and other AWS services for your end-to-end ML development, from prepare data at peta-byte scale using Spark on Amazon EMR, train and debug models, track experiments, deploy and monitor models and manage pipelines – all in Amazon SageMaker Studio – a fully integrated development environment (IDE) for ML. Easily dial up or down compute resources without interrupting your work. Share notebooks easily with your team using a sharable link.

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#MachineLearning #SageMaker #JupyterNotebook #SageMakerStudio #AWS #AmazonWebServices #CloudComputing