Setting up human review of your NLP-based entity recognition models with Amazon SageMaker Ground Truth, Amazon Comprehend, and Amazon A2I

Organizations across industries have a lot of unstructured data that you can evaluate to get entity-based insights. You may also want to add your own entity types unique to your business, like proprietary part codes or industry-specific terms. To create a natural language processing (NLP)-based model, you need to label

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Shared by AWS Machine Learning July 24, 2020

Free access to knowledge, or structured access to knowledge?

Here is another excellent article from Tom Davenport, one of the clearest writers on the topic of Knowledge Management, making the case for a structured “just-in-time” approach to the supply of knowledge.  Tom starts his article as follows: In the half-century since Peter Drucker coined the term “knowledge workers,” their

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Shared by Nick Milton July 23, 2020

Translating presentation files with Amazon Translate

As solutions architects working in Brazil, we often translate technical content from English to other languages. Doing so manually takes a lot of time, especially when dealing with presentations—in contrast to plain text documents, their content is spread across various areas in multiple slides. To solve that, we wrote a

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Shared by AWS Machine Learning July 22, 2020

Deploying TensorFlow OpenPose on AWS Inferentia-based Inf1 instances for significant price performance improvements

In this post you will compile an open-source TensorFlow version of OpenPose using AWS Neuron and fine tune its inference performance for AWS Inferentia based instances. You will set up a benchmarking environment, measure the image processing pipeline throughput, and quantify the price-performance improvements as compared to a GPU based

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Shared by AWS Machine Learning July 22, 2020

Query drug adverse effects and recalls based on natural language using Amazon Comprehend Medical

In this post, we demonstrate how to use Amazon Comprehend Medical to extract medication names and medical conditions to monitor drug safety and adverse events. Amazon Comprehend Medical is a natural language processing (NLP) service that uses machine learning (ML) to easily extract relevant medical information from unstructured text. We query the OpenFDA

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Shared by AWS Machine Learning July 21, 2020