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Amazon SageMaker Studio

Amazon SageMaker Studio

A single web-based interface for end-to-end AI model development

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Why SageMaker Studio?

Amazon SageMaker Studio offers a wide choice of purpose-built tools to perform all AI model development steps, from preparing data to building, training, deploying, and managing your AI models. You can quickly upload data and build models using your preferred integrated development environment (IDE). Streamline team collaboration, code efficiently using the AI-powered coding companion, tune and debug models, deploy and manage models in production, and automate workflows—all within a single, unified web-based interface.

Screenshot of the Amazon SageMaker Studio dashboard, showing an overview of available workflows, applications like JupyterLab and Code Editor, prebuilt solutions such as JumpStart and AutoML, and navigation for data, experiments, models, and deployments.

Benefits of SageMaker Studio

Develop AI models using fully managed cloud IDEs or a local IDE. Quickly launch your preferred fully managed IDEs, including JupyterLab, Code Editor based on Code-OSS (VS Code Open Source), and RStudio, and scale the underlying compute resources dynamically based on your needs. In addition, develop AI models using your local Visual Studio Code while leveraging the SageMaker AI scalable compute resources.

Access the most comprehensive set of tools for each step of your AI model development, from preparing data to building, training, deploying, and managing models. Quickly move between steps to fine-tune your models, replay training experiments, and directly scale to distributed training from JupyterLab, Code Editor, or RStudio on SageMaker AI. Build faster with our generative AI–powered assistant, integrated into your workflow. Our AI assistant supports your entire AI model development journey in real time, all within your notebook environment.

Build generative AI applications with access to hundreds of popular publicly available models and over 15 prebuilt solutions through Amazon SageMaker JumpStart. You can access models from top model providers such as AI21 Labs, LightOn, Stability AI, Hugging Face, Alexa, and Meta AI. Then quickly evaluate, compare, and select the best foundation models (FMs) for your use case based on predefined metrics such as accuracy, robustness, and toxicity. Human evaluations can be used for more subjective dimensions such as creativity and style.

You can use SageMaker Studio from any device using a web browser. Both code and data are kept within your secure cloud environment with no need to download sensitive artifacts to your local machine.

Accelerate your model development with popular apps from AWS Partners. Use a seamless and fully managed experience with no infrastructure to provision or operate, all within the security and privacy of your SageMaker AI environment.

Use cases

Build generative AI applications faster with access to a wide range of publicly available FMs, model evaluation tools, IDEs backed by high-performance accelerated computing, and the ability to directly fine-tune and deploy FMs at scale from SageMaker Studio.

Unify your end-to-end AI model development in SageMaker Studio with the most comprehensive tools all in one place. SageMaker AI offers high-performing MLOps tools to help you automate and standardize workflows and governance tools to support transparency and auditability across your organization.

SageMaker Studio offers a unified experience to perform all data analytics and model workflows. Create, browse, and connect to Amazon EMR clusters. Build, test, and run interactive data preparation and analytics applications with AWS Glue interactive sessions. Monitor and debug Spark jobs using familiar tools such as Spark UI—all right from SageMaker Studio.

AI apps from AWS Partners

Access industry-leading apps in a secure, managed environment to accelerate your generative AI and ML development.

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