From the course: Generative AI and Large Language Models on AWS

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SageMaker Code editor

SageMaker Code editor - Amazon Web Services (AWS) Tutorial

From the course: Generative AI and Large Language Models on AWS

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SageMaker Code editor

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- [Instructor] Here we have SageMaker Studio, which is a full fledged environment for dealing with machine learning and also working with large language models. You can see on the left here, there's a lot of stuff going on. So we have the ability to launch Jupyter Lab, our Studio Canvas code editor. We also have this Studio classic, which is an older version. And if we take a look at the different tabs here as well, we have running instances, data, auto ML experiments, jobs, pipelines, models, jumpstart, deployments, right? So basically full MLops pipeline here. The one that I'm the most interested in demoing right now, though, is code editor. Very new feature and it has a Visual Studio Code open source editor, and you can test, debug, and run the analytics and ML code right inside of the browser, and it has the full IDE extension available in the open VSX extension registry. So if we take a look at how this works here, notice here we have this demo environment and you could stop it…

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