Amazon SageMaker Studio is a fully-managed, cloud-based integrated development environment (IDE) designed for data scientists, machine learning (ML) practitioners, and AI developers. It allows users to quickly and easily create, train, and deploy ML models on AWS without having to manage infrastructure. The Studio environment provides users with a single, web-based IDE that encompasses the entire ML workflow: data exploration and visualization, preprocessing, model building, and deployment.
Data scientists can take advantage of the integrated development environment and tools that Amazon SageMaker Studio provides in order to achieve a variety of data science tasks, including:
-Interactive exploration and visualization of data
-Pre-processing of data for ML and deep learning
-Building, deploying, and managing machine learning models
-Monitoring model performance
-Using and managing Jupyter Notebooks
-Integration with popular tools such as Amazon SageMaker Autopilot, Amazon Augmented AI, and the AWS Tools for Windows PowerShell.
Amazon SageMaker Studio is suitable for all levels of ML practitioners, from beginner to advanced. It provides data scientists with an intuitive and powerful environment in which to create, manage, and deploy ML models. Through its integrated tools and pre-built templates, Amazon SageMaker Studio is able to speed up model development and deployment, while helping to ensure accuracy and scalability.
This is a Rare Course and it can be take up to 3 weeks to arrange the training.