What is SageMaker notebooks?
Launch fully managed JupyterLab from Amazon SageMaker Studio in seconds. Use the integrated development environment (IDE) for notebooks, code, and data. You can use the quick start, collaborative notebooks in the IDE to access purpose-built ML tools in SageMaker and other AWS services for your complete ML development, from preparing data at petabyte scale using Spark on Amazon EMR, to training and debugging models, deploying and monitoring models and managing pipelines – all in one web-based visual interface. Easily dial compute resources up or down without interrupting your work.
Benefits of SageMaker notebooks
Build ML at scale
Quick start
Elastic compute
Boost ML development productivity
Data preparation
Notebook jobs
AI-powered tools
Amazon CodeWhisperer is an AI coding companion that generates real-time code suggestions. With CodeWhisperer, you can write a comment in natural language that outlines a specific task, such as “Create a pandas dataframe using a CSV file”, and CodeWhisperer recommends one or more code snippets directly in the notebook that can accomplish the task. Amazon CodeGuru Security assists notebook users in detecting security vulnerabilities such as injection flaws, data leaks, weak cryptography, or missing encryption within the notebook cells. When vulnerabilities or quality issues are identified, CodeGuru generates recommendations to remediate those issues based on AWS security best practices.