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Favorite Feature engineering is a process of applying transformations on raw data that a machine learning (ML) model can use. As an organization scales, this process is typically repeated by multiple teams that use the same features for different ML solutions. Because of this, organizations are forced to develop their
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Shared by AWS Machine Learning July 21, 2021
Favorite Amazon Personalize now enables you to tap into the information trapped in product descriptions, product reviews, movie synopses, or other unstructured text and use it when generating personalized recommendations. Product descriptions provide important information about the features and benefits of products. Amazon Personalize can use the investments made to
Read More Shared by AWS Machine Learning July 20, 2021
Favorite 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
Read More Shared by AWS Machine Learning July 20, 2021
Favorite 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
Read More Shared by AWS Machine Learning July 20, 2021
Favorite 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
Read More Shared by AWS Machine Learning July 17, 2021
Favorite 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
Read More Shared by AWS Machine Learning July 17, 2021
Favorite 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
Read More Shared by AWS Machine Learning July 16, 2021
Favorite 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,
Read More Shared by AWS Machine Learning July 16, 2021
Favorite 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
Read More Shared by AWS Machine Learning July 16, 2021
Favorite Anomaly detection is the process of identifying items, events, or occurrences that have different characteristics from the majority of the data. It has many applications in various fields, like fraud detection for credit cards, insurance, or healthcare; network intrusion detection for cybersecurity; KPI metrics monitoring for critical systems; and
Read More Shared by AWS Machine Learning July 14, 2021