Amazon SageMaker overview | Amazon Web Services

Опубликовано 6 июня 2024, 22:24

Amazon SageMaker Studio offers a wide choice of purpose-built tools to perform all machine learning (ML) development steps, from preparing data to building, training, deploying, and managing your ML models. This demo video starts with an overview of SageMaker Studio's popular applications and tooling for building generative AI and machine learning models, and then provides a deep dive into JumpStart and JupyterLab. JumpStart is a generative AI and ML hub offering models, algorithms, and pre-built ML solutions. It offers hundreds of ready-to-use foundation models from various model providers and allows you to fine tune LLMs on your own dataset with no code experience, and deploy LLMs with one click. JupyterLab enables you to connect to and browse data sources like Redshift, Athena, and Snowflake and easily query data in your notebook using SQL. With JupyterLab, you can collaborate with your teammates in shared JupyterLab spaces, operationalize your JupyterLab notebooks, and connect to EMR and Glue for Spark processing.

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