Amazon SageMaker Studio

Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning that lets you build, train, debug, deploy, and monitor your machine learning models. SageMaker Studio provides all the tools you need to take your models from data preparation to experimentation to production while boosting your productivity. In a single unified visual interface, customers can perform the following tasks:

• Write and execute code in Jupyter notebooks

• Prepare data for machine learning

• Build and train machine learning models

• Deploy the models and monitor the performance of their predictions

• Track and debug the machine learning experiments

For information on the onboarding steps to sign in to SageMaker Studio, see Onboard to Amazon SageMaker Domain.

For the AWS Regions supported by SageMaker Studio, see Supported Regions and Quotas.

Topics

• Studio Features
• Amazon SageMaker Studio UI Overview
• Launch Amazon SageMaker Studio
• JupyterLab Versioning
• Use the Amazon SageMaker Studio Launcher
• Use Amazon SageMaker Studio Notebooks
• Customize Amazon SageMaker Studio
• Perform Common Tasks in Amazon SageMaker Studio
• Amazon SageMaker Studio Pricing
• Troubleshooting Amazon SageMaker Studio

Studio Features

Studio includes the following features:

• SageMaker Autopilot

• SageMaker Clarify

• SageMaker Data Wrangler

• SageMaker Debugger

• SageMaker Experiments

• SageMaker Feature Store

• SageMaker JumpStart

• Amazon SageMaker Model Building Pipelines

• SageMaker Model Registry

• SageMaker Projects

• SageMaker Studio Notebooks

• SageMaker Studio Universal Notebook