Amazon SageMaker now supports geospatial ML (preview)
Amazon SageMaker now supports geospatial machine learning (ML), making it easier for data scientists and ML engineers to build, train, and deploy models using geospatial data. Today, the majority of all data generated contains geospatial information, but only a small fraction of it is used for ML because accessing, processing, and visualizing the data is complex, time consuming, and expensive.
Amazon SageMaker now supports geospatial machine learning (ML), making it easier for data scientists and ML engineers to build, train, and deploy models using geospatial data. Today, the majority of all data generated contains geospatial information, but only a small fraction of it is used for ML because accessing, processing, and visualizing the data is complex, time consuming, and expensive.
SageMaker’s new geospatial capabilities simplify the process of building, training, and deploying models with geospatial data. You can now access readily available geospatial data sources, efficiently process or enrich large-scale geospatial datasets with purpose-built operations, and accelerate model building by selecting pretrained ML models. You can then analyze and explore the generated predictions on an interactive map within SageMaker and share and collaborate on results. You can use SageMaker geospatial capabilities for a wide range of use cases, such as supporting sustainable urban development, maximizing harvest yield and food security, assessing risk and insurance claims, and predicting retail demand.
Amazon SageMaker support for geospatial ML is now available in preview in the US West (Oregon) Region.
To learn more about geospatial ML capabilities, visit the webpage, view our documentation, or read our blog post.