Source: thenewstack.io
Amazon SageMaker Studio Lab from the Eyes of an MLOps EngineerCategory: Software, Data, Docker, shell, artificial-intelligence
At the https://aws.amazon.com/?utm_content=inline-mention‘ re:Invent 2021 conference, an announcement from https://www.linkedin.com/in/swaminathansivasubramanian, Vice President for Amazon AI, caught my attention — the launch of https://studiolab.sagemaker.aws/. Since the initial launch of the https://aws.amazon.com/about-aws/whats-new/2015/04/introducing-amazon-machine-learning/ at re:Invent 2015, AWS has constantly improved the managed ML platform and tools.
Amazon SageMaker Studio Lab is unique in many aspects.
Simply put, SageMaker Studio Lab is a JupyterLab application running in a pre-provisioned Amazon EC2 instance.
With inbuilt support for git and the availability of the AWS CLI, it’s easy to connect the platform with external environments, including Amazon SageMaker Studio.
Amazon SageMaker Studio Lab is unique in many aspects.
Simply put, SageMaker Studio Lab is a JupyterLab application running in a pre-provisioned Amazon EC2 instance.
With inbuilt support for git and the availability of the AWS CLI, it’s easy to connect the platform with external environments, including Amazon SageMaker Studio.
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