Amazon SageMaker Studio

A single web-based interface for end-to-end ML development
Get started with Amazon SageMaker AI
Explore the Amazon SageMaker Unified Studio

Why SageMaker Studio?

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. You can quickly upload data and build models using your preferred IDE. Streamline ML 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.

SageMaker Studio

Benefits of SageMaker Studio

Amazon SageMaker Studio offers a broad set of fully managed integrated development environments (IDEs) for machine learning (ML) development, including JupyterLab, Code Editor based on Code-OSS (Visual Studio Code – Open Source), and RStudio. Launch your preferred IDE quickly and scale the underlying compute up and down on the fly.
Access the most comprehensive set of tools for each step of ML development, from preparing data to building, training, deploying, and managing ML 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 Amazon Q Developer, a generative AI–powered assistant integrated into your workflow. Amazon Q Developer assists you across your entire ML 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 ML artifacts to your local machine.
Accelerate your model development with popular apps from AWS partners. Seamless and fully managed experience with no infrastructure to provision or operated. All within the security and privacy of your SageMaker 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 fine tune and deploy FMs at scale directly from SageMaker Studio.

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

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