Increase ML Development Productivity with Notebook Instances on Amazon SageMaker

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Published Feb 20, 2025

Amazon SageMaker helps data scientists and developers to prepare data, build, train, and deploy high-quality ML models quickly by bringing together a broad set of capabilities purpose-built for ML. Join us as we walk through a hands-on demo of what you can do with SageMaker Notebook Instances, which now come with JupyterLab 3, bringing you the latest JupyterLab capabilities to boost ML development productivity. In addition to Notebook Instances, you will also see how to manage training jobs and models using SageMaker Experiments and Model Registry.

Learning Objectives:
* Objective 1: SageMaker Notebook Instances features demo, including JupyterLab 3.
* Objective 2: Managing training jobs using SageMaker Experiments.
* Objective 3: Managing models using SageMaker Model Registry.

***To learn more about the services featured in this talk, please visit: https://aws.amazon.com/sagemaker/notebooks
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