Code assistance integration with Amazon SageMaker
Before we start diving deep into code assistance support for the Amazon SageMaker service, let’s quickly go through an overview of Amazon SageMaker. Amazon SageMaker is a fully managed service that simplifies the process of building, training, and deploying ML models at scale. It is designed to make it easier for developers and data scientists to build, train, and deploy ML models without the need for extensive expertise in ML or deep learning. It has multiple features such as end-to-end workflow, built-in algorithms, custom model training, automatic model tuning, ground truth, edge manager, augmented AI, and managed notebooks, just to name a few. Amazon SageMaker integrates with other AWS services, such as Amazon S3 for data storage, AWS Lambda for serverless inference, and Amazon CloudWatch for monitoring.
Amazon SageMaker Studio hosts the managed notebooks, which are integrated with Amazon Q Developer.
