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

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

Favorite Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). With a single click, data scientists and developers can quickly spin up Studio notebooks to explore and prepare datasets to build, train, and deploy ML models in a single pane of glass. We’re excited

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Shared by AWS Machine Learning September 17, 2021

Favorite Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). With a single click, data scientists and developers can quickly spin up Studio notebooks to explore and prepare datasets to build, train, and deploy ML models in a single pane of glass. We’re excited

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Shared by AWS Machine Learning September 17, 2021

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

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

Favorite Think about the last time you opened a bank account, applied for insurance, or refinanced your home. It was probably done on paper. The number of documents in a mortgage packet alone is over 100 pages long. What do you do with all that paper? For many companies across

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Shared by AWS Machine Learning September 15, 2021

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

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

Favorite Amazon SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps, improving data science team productivity by up to 10 times. Studio gives you complete access, control, and visibility into each step required to build, train, and deploy models. You can quickly upload

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Shared by AWS Machine Learning September 15, 2021