Posted On: Feb 11, 2022

Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). With a single click, data scientists and developers can quickly spin up SageMaker Studio Notebooks to interactively explore datasets and build ML models. The notebooks come pre-configured with deep learning environments for Amazon Web Services-optimized TensorFlow and PyTorch to quickly get started with building models. Starting today you can access two new environments for TensorFlow 2.6 and PyTorch 1.8.

Data preparation is a foundational step of any data science and ML workflow. Therefore, the new TensorFlow 2.6 and PyTorch 1.8 environments come built-in with the recently introduced capability to visually browse and connect to Amazon EMR clusters right from the SageMaker Studio Notebook. Thus, you can interactively explore, visualize and prepare petabyte-scale data using Spark, Hive and Presto on Amazon EMR and build ML models using the latest deep learning frameworks without leaving the notebook.

These new data analytics capabilities in SageMaker Studio are generally available in both Amazon Web Services China (Beijing) Region, operated by Sinnet, and Amazon Web Services China (Ningxia) Region, operated by NWCD. To learn more about SageMaker Studio visit the SageMaker user guide.