AWS Machine Learning Blog

Category: Artificial Intelligence

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

Update Aug 12, 2020 – New features: Amazon Comprehend adds five new languages(Spanish, French, German, Italian and Portuguese) read here. Amazon Comprehend increased the limit of number of entities per custom entity model from 12 to 25 read here. Organizations across industries have a lot of unstructured data that you can evaluate to get entity-based […]

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Extracting custom entities from documents with Amazon Textract and Amazon Comprehend

Amazon Textract is a machine learning (ML) service that makes it easy to extract text and data from scanned documents. Textract goes beyond simple optical character recognition (OCR) to identify the contents of fields in forms and information stored in tables. This allows you to use Amazon Textract to instantly “read” virtually any type of […]

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Increasing engagement with personalized online sports content

This is a guest post by Mark Wood at Pulselive. In their own words, “Pulselive, based out of the UK, is the proud digital partner to some of the biggest names in sports.” At Pulselive, we create experiences sports fans can’t live without; whether that’s the official Cricket World Cup website or the English Premier […]

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Deploying custom models built with Gluon and Apache MXNet on Amazon SageMaker

When you build models with the Apache MXNet deep learning framework, you can take advantage of the expansive model zoo provided by GluonCV to quickly train state-of-the-art computer vision algorithms for image and video processing. A typical development environment for training consists of a Jupyter notebook hosted on a compute instance configured by the operating […]

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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 instance. About OpenPose Human pose […]

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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 script that translates Microsoft PowerPoint […]

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Atlassian continuously profiles services in production with Amazon CodeGuru Profiler

This is a guest post by the Jira Cloud Performance Team at Atlassian. In their own words, Atlassian’s mission is to unleash the potential in every team. Our products help teams organize, discuss, and complete their work. And what teams do can change the world. We have helped NASA teams design the Mars Rover, Cochlear teams develop […]

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YoucanBook.me optimizes your apps thanks to Amazon CodeGuru

This is a guest post co-written by Sergio Delgado from YoucanBook.me. In their own words, “YouCanBook.me is a small, independent and fully remote team, who love solving scheduling problems all over the world.” At YoucanBook.me, we like to say that we’re “a small company that does great things.” Many aspects of our day-to-day culture are […]

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Infoblox Inc. built a patent-pending homograph attack detection model for DNS with Amazon SageMaker

This post is co-written by Femi Olumofin, an analytics architect at Infoblox. In the same way that you can conveniently recognize someone by name instead of government-issued ID or telephone number, the Domain Name System (DNS) provides a convenient means for naming and reaching internet services or resources behind IP addresses. The pervasiveness of DNS, […]

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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 API (an open-source API published by […]

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