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Getting started to learn and experiment ML with Amazon SageMaker Studio Lab

March 22, 2022

Amazon SageMaker Studio Lab offers an open-source Jupyter notebook environment integrated with the GitHub software development platform and preconfigured with the most popular ML tools, frameworks, and libraries so that you can write ML code immediately without having to configure the ML environment. Using Amazon SageMaker Studio Lab, you can work on ML projects without worrying about saving models. It’s as easy as closing your laptop and coming back later. In this session, learn how Amazon SageMaker Studio Lab is accelerating your journey on machine learning with a free machine learning (ML) development environment that provides the compute, storage (up to 15GB), and security—all at no cost—for anyone to learn and experiment with ML. All you need to get started is a valid email address—you do not need to configure infrastructure or manage identity and access or even sign up for an AWS account.

Speaker: Donnie Prakoso, Senior Developer Advocate, AWS

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