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.
Learn ML with SageMaker Studio Lab
Learn and experiment with ML using a no-setup, free development environment
Explore SageMaker Studio
SageMaker Studio provides a single, web-based visual interface where you can perform all ML steps, improving data science team productivity.
Get started faster with SageMaker JumpStart
Pre-built ML algorithms, models, and solutions that you can deploy with just a few clicks