Use the AWS Cloud for observational life sciences studies

Favorite In this post, we discuss how to use the AWS Cloud and its services to accelerate observational studies for life sciences customers. We provide a reference architecture for architects, business owners, and technology decision-makers in the life sciences industry to automate the processes in clinical studies. Observational studies lead

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Shared by AWS Machine Learning September 20, 2021

How remote working makes organisations more siloed

Favorite  A new study published in Nature shows that hybrid or remote working leads to a loss of collaboration across the organisational siloes, which is likely to inhibit the flow of knowledge. The study is called “The effects of remote work on collaboration among information workers“, with 9 authors, and

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Shared by Nick Milton September 20, 2021

Arçelik hosts global AWS DeepRacer League using new LIVE feature to educate over 200 employees on machine learning

Favorite This is a guest post by Pınar Köse Kulacz, Innovation Director at Arçelik. Arçelik, the leading global manufacturer of household appliances, has collaborated with AWS since 2019 to increase efficiency and innovate on new services. Here at Arçelik, we believe that data and artificial intelligence provide a critical advantage

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Shared by AWS Machine Learning September 18, 2021

Train fraudulent payment detection with Amazon SageMaker

Favorite The ability to detect fraudulent card payments is becoming increasingly important as the world moves towards a cashless society. For decades, banks have relied on building complex mathematical models to predict whether a given card payment transaction is likely to be fraudulent or not. These models must be both

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Shared by AWS Machine Learning September 17, 2021

Train fraudulent payment detection with Amazon SageMaker

Favorite The ability to detect fraudulent card payments is becoming increasingly important as the world moves towards a cashless society. For decades, banks have relied on building complex mathematical models to predict whether a given card payment transaction is likely to be fraudulent or not. These models must be both

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Shared by AWS Machine Learning September 17, 2021

Extract custom entities from documents in their native format with Amazon Comprehend

Favorite Multiple industries such as finance, mortgage, and insurance face the challenge of extracting information from documents and taking a specific action to enable business processes. Intelligent document processing (IDP) helps extract information locked within documents that is important to business operations. Customers are always seeking new ways to use

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Shared by AWS Machine Learning September 15, 2021

Custom document annotation for extracting named entities in documents using Amazon Comprehend

Favorite Intelligent document processing (IDP), as defined by IDC, is an approach by which unstructured content and structured data is analyzed and extracted for use in downstream applications. IDP involves document reading, categorization, and data extraction, by using AI’s processes of computer vision (CV), Optical Character Recognition (OCR), and natural

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Shared by AWS Machine Learning September 15, 2021