A Technology Broker and Management Company Specializing in KM Systems
Amazon SageMaker Feature Store is a purpose-built solution for machine learning (ML) feature management. It helps data science teams reuse ML features across teams and models, serves features for model predictions at scale with low latency, and train and deploy new models more quickly and effectively. As you learn about
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Shared by AWS Machine Learning September 20, 2021
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 the
Read More Shared by AWS Machine Learning September 20, 2021
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 was
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Shared by Nick Milton September 20, 2021
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 over
Read More Shared by AWS Machine Learning September 18, 2021
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 to
Read More Shared by AWS Machine Learning September 17, 2021
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 to
Read More Shared by AWS Machine Learning September 17, 2021
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 accurate
Read More Shared by AWS Machine Learning September 17, 2021
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 accurate
Read More Shared by AWS Machine Learning September 17, 2021
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 a
Read More Shared by AWS Machine Learning September 15, 2021
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 artificial
Read More Shared by AWS Machine Learning September 15, 2021
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