1 year ago

https://aws.amazon.com/polly/ In 2019, we https://aws.amazon.com/blogs/aws/amazon-sagemaker-studio-the-first-fully-integrated-development-environment-for-machine-learning/, the first fully integrated development environment (IDE) for data science and machine learning (ML). SageMaker Studio gives you access to fully managed https://jupyter.org/ Notebooks that integrate with purpose-built tools to perform all ML steps, from preparing data to training and debugging models, tracking experiments, deploying and monitoring models, and managing pipelines.

New Notebook Capability for Simplified Data Preparation The new built-in data preparation capability is powered by Amazon SageMaker Data Wrangler and is available in SageMaker Studio notebooks.

Once you apply a data transformation, SageMaker Studio notebooks automatically generate the code to reproduce those data preparation steps in another notebook cell.

Introducing Shared Spaces for Team-Based Sharing and Real-Time Collaboration SageMaker Studio now offers shared spaces that give data science and ML teams a workspace where they can read, edit, and run notebooks together in real time to streamline collaboration and communication during the development process.