AWS Expands SageMaker to Bring Machine Learning to Business Users
AWS announces several new Amazon SageMaker features at re:Invent 2021 that make machine learning accessible to non-technical business analysts while improving performance and reducing costs for experts.
AWS announces a suite of new Amazon SageMaker features at re:Invent 2021 that make machine learning accessible to a wider audience. These updates aim to extend ML capabilities beyond data scientists and developers to business analysts in finance, marketing, operations, and HR departments who lack coding experience.
To empower non-technical users, AWS introduces Amazon SageMaker Canvas, a visual point-and-click interface that allows business analysts to generate accurate ML predictions without writing any code. Additionally, the company launches Amazon SageMaker Ground Truth Plus, a fully managed data labeling service that provides an expert workforce to handle the growing demand for high-quality training datasets without requiring companies to build their own labeling applications.
For data scientists and developers, AWS enhances Amazon SageMaker Studio by uniting data processing, analytics, and ML workflows into a single unified notebook. This consolidated environment allows users to connect to various data sources and write transformation code for diverse workloads, ultimately optimizing the performance and cost of building, training, and deploying ML models.