Machine learning (ML) provides innovation for every business. Until recently, developing ML models took time and effort, making it difficult for developers to get started. In this session, we demonstrate how Amazon SageMaker—a fully managed service that enables developers to build, train, and deploy ML models at scale—overcomes those barriers. We review its capabilities across data labeling, model building, model training, tuning, and production hosting. Additionally, Workday—a provider of enterprise cloud applications for human capital management, financial management, and analytics—discusses how it accelerated ML throughout its organization, benefits gained, and why it standardized on Amazon SageMaker.