Machine Learning - eBook (EN)

7 leading machine learning use cases at scale

Issue link: https://read.uberflip.com/i/1491606

Contents of this Issue

Navigation

Page 13 of 13

It's time to embrace machine learning By using purpose-built development and data tools, MLOps, no-code ML, infrastructure, and solutions focused on responsible use of data and models on a fully managed service, you can propel many more models from concept to production in a repeatable way for less cost. Amazon SageMaker outpaces time-consuming, difficult, and expensive self-managed ML platforms to help you: • Reduce total cost of ownership by 54 percent • Achieve more than 10 times greater productivity • Perform over 100 billion predictions per month • Cut data labeling costs by 40 percent • Accelerate model training by up to 50 percent through more efficient use of GPUs And with 22 compliance programs (including PCI, HIPAA, SOC, 1/2/3, FedRAMP, and ISO), AWS can help you gain the swiftness and security that powers your business into the future. Learn more about SageMaker for high-performance, low-cost ML development at scale › 2023, Amazon Web Services, Inc. or its affiliates. All rights reserved.

Articles in this issue

Links on this page

view archives of Machine Learning - eBook (EN) - 7 leading machine learning use cases at scale