Amazon SageMaker enables ML savings
At this stage, the viability and effectiveness of machine learning for tasks like classification, regression, and image recognition is well-documented across industry and academia. As more organizations look to leverage these capabilities, a primary challenge is managing the data, models, and infrastructure in an efficient and agile manner. Since these businesses have migrated workloads to the cloud, cloud vendors like AWS recognized the opportunity to deliver additional value in the form of managed machine learning (ML) services. In 2017, AWS announced Amazon SageMaker, a fully managed service for the creation, training, and deployment of machine learning models. In examining companies who have deployed SageMaker, Nucleus has found the key benefits include an accelerated development cycle, cost savings, increased developer productivity, and increased machine learning agility.