Amazon Sagemaker Studio, a part of the SageMaker umbrella of services, is an IDE for ML that provides a single unified interface for all the tools, including Jupyter notebooks and RStudio, you need to take your models from experimentation to production and boost your productivity. SM Studio provides access to all ML resources in one place.

In this session, we will provide an overview of SM studio and its features: Data preparation and Feature Engineering using Data Wrangler, Build ML models using Jupyter notebooks, Train and Deploy models.

Instructor: AWS Solutions Architect Team