SageMaker Studio, which is based on JupyterLab, is said to provide a visual interface for all ML development steps.
Its availability has been extended to an additional 13 regions, including Asia Pacific (Hong Kong), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo).
Local SageMaker customers include Transport for NSW, which has used it to determine how the weather impacts public transport use and thus better predict patronage numbers across the transport network.
"With the launch of Amazon SageMaker Studio in the AWS Asia Pacific (Sydney) Region, we are helping our customers to manage all the pieces needed to build, train, explain, inspect, monitor, debug, and run custom machine learning models all in one place." said AWS ANZ director of public sector technology and transformation Simon Elisha.
"AWS offers the broadest and deepest set of machine learning services available in the cloud, and we are looking forward to seeing how our local customers use Amazon SageMaker Studio to continue to innovate and improve their customer experiences."