AWS Machine Learning Blog

You might use traditional methods to forecast future business outcomes, but these traditional methods are often not flexible enough to account for varying factors, such as weather or promotions, outside of the traditional time series data considered. With the advancement of machine learning (ML) and the elasticity that the AWS Cloud brings, you can now […]

Have you noticed that your shopping preferences are influenced by the weather? For example, on hot days would you rather drink a lemonade vs. a hot coffee? Customers from consumer-packaged goods (CPG) and retail industries wanted to better understand how weather conditions like temperature and rain can be used to provide better purchase suggestions to […]

In Part 1 of this series, we walk through a continuous model improvement machine learning (ML) workflow with Amazon Rekognition Custom Labels and Amazon Augmented AI (Amazon A2I). We explained how we use AWS Step Functions to orchestrate model training and deployment, and custom label detection backed by a human labeling private workforce. We described […]

If you need to integrate image analysis into your business process to detect objects or scenes unique to your business domain, you need to build your own custom machine learning (ML) model. Building a custom model requires advanced ML expertise and can be a technical challenge if you have limited ML knowledge. Because model performance […]

This post was last reviewed and updated June, 2022. When this blog post was initially published, English was the only language supported for the textual field in the items dataset. Now Amazon Personalize supports textual field values in Chinese (simplified and traditional), French, German, Japanese, Portuguese, and Spanish; removes HTML and XML markup and whitespace […]

AWS just announced the General Availability of Amazon HealthLake, a HIPAA-eligible service for healthcare providers, health insurance companies, and pharmaceutical companies to securely store, transform, query, analyze, and share health data in the cloud at petabyte scale. We believe that the combination of the innovation trends in healthcare (such as reimbursement models around data-driven evidence), […]

Healthcare technology companies often turn to AWS to help them accelerate their clinical and business objectives. MEDHOST has provided enterprise information technology and electronic health record (EHR) solutions to full-service community hospitals for more than 35 years. Today, more than 1,000 healthcare facilities are partnering with MEDHOST and enhancing their patient care and operational excellence […]

For many enterprises, critical business information is often stored as unstructured data scattered across multiple content repositories. It is challenging for organizations to make this information available to users when they need it. It is also difficult to do so securely so that relevant information is available to the right users or user groups. Different […]

Amazon HealthLake is a new HIPAA-eligible service designed to store, transform, query, and analyze health data at scale. Amazon HealthLake removes the heavy lifting of organizing, indexing, and structuring patient information to provide a complete view of the health of individual patients and entire patient populations in a secure, compliant, and auditable manner. With the […]

Amazon HealthLake is a new, HIPAA-eligible service designed to store, transform, query, and analyze health data at scale. You can bring your healthcare data into Amazon HealthLake using Fast Healthcare Interoperability Resources (FHIR) R4 APIs. If you don’t have your data in FHIR R4, Amazon has collaborated with industry experts to build Amazon HealthLake connectors […]