Amazon SageMaker for Data Scientists

Integrated development environment (IDE) for the ML lifecycle

Access data from structured and unstructured data sources

Improve productivity with purpose-built tools

Use fully managed Jupyter Notebooks with just a few clicks

Easily prepare data, and build, train, and deploy ML models

Data science is the study of data to extract meaningful insights for business. It asks and answers questions such as what happened, why it happened, and what will happen. Machine learning (ML) is essential for data science because ML makes it practical for machines to solve problems that traditional analytics cannot easily solve with rule-based logic. ML analyzes data and discovers patterns by learning from examples. Machines can then use the patterns to recognize unknown instances. Amazon SageMaker offers a broad set of ML capabilities used by tens of thousands of customers to access and analyze data, and build, train, and deploy high-quality ML models. Your data science teams can be up to 10 times more productive using SageMaker.

Amazon SageMaker for Data Scientists

Learn ML with SageMaker Studio Lab

Learn and experiment with ML using a no-setup, free development environment

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Explore SageMaker Studio

SageMaker Studio provides a single, web-based visual interface where you can perform all ML steps, improving data science team productivity.

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Get started faster with SageMaker JumpStart

Pre-built ML algorithms, models, and solutions that you can deploy with just a few clicks

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