AWS Machine Learning Blog

Category: Amazon Augmented AI

Focusing on disaster response with Amazon Augmented AI and Mechanical Turk

It’s easy to distinguish a lake from a flood. But when you’re looking at an aerial photograph, factors like angle, altitude, cloud cover, and context can make the task more difficult. And when you need to identify 100,000 aerial images in order to give first responders the information they need to accelerate disaster response efforts? […]

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Amazon Augmented AI is now a HIPAA eligible service

Amazon Augmented AI (Amazon A2I) is now a HIPAA eligible service. Amazon A2I makes it easy to build the workflows required for human review of machine learning (ML) predictions. HIPPA eligibility applies to AWS Regions where the service is available and means you can use Amazon A2I add human review of protected health information (PHI) […]

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Building an end-to-end intelligent document processing solution using AWS

As organizations grow larger in size, so does the need for having better document processing. In industries such as healthcare, legal, insurance, and banking, the continuous influx of paper-based or PDF documents (like invoices, health charts, and insurance claims) have pushed businesses to consider evolving their document processing capabilities. In such scenarios, businesses and organizations […]

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Using Amazon Rekognition Custom Labels and Amazon A2I for detecting pizza slices and augmenting predictions

Customers need machine learning (ML) models to detect objects that are interesting for their business. In most cases doing so is hard as these models need thousands of labeled images and deep learning expertise.  Generating this data can take months to gather, and can require large teams of labelers to prepare it for use. In […]

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Architecture Diagram for Feedback Loops

Active learning workflow for Amazon Comprehend custom classification models – Part 1

Amazon Comprehend  Custom Classification API enables you to easily build custom text classification models using your business-specific labels without learning ML. For example, your customer support organization can use Custom Classification to automatically categorize inbound requests by problem type based on how the customer has described the issue.  You can use custom classifiers to automatically label […]

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Build alerting and human review for images using Amazon Rekognition and Amazon A2I

The volume of user-generated content (UGC) and third-party content has been increasing substantially in sectors like social media, ecommerce, online advertising, and photo sharing. However, such content needs to be reviewed to ensure that end-users aren’t exposed to inappropriate or offensive material, such as nudity, violence, adult products, or disturbing images. Today, some companies simply […]

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Automated monitoring of your machine learning models with Amazon SageMaker Model Monitor and sending predictions to human review workflows using Amazon A2I

When machine learning (ML) is deployed in production, monitoring the model is important for maintaining the quality of predictions. Although the statistical properties of the training data are known in advance, real-life data can gradually deviate over time and impact the prediction results of your model, a phenomenon known as data drift. Detecting these conditions […]

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Improving speech-to-text transcripts from Amazon Transcribe using custom vocabularies and Amazon Augmented AI

Businesses and organizations are increasingly using video and audio content for a variety of functions, such as advertising, customer service, media post-production, employee training, and education. As the volume of multimedia content generated by these activities proliferates, businesses are demanding high-quality transcripts of video and audio to organize files, enable text queries, and improve accessibility […]

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Processing PDF documents with a human loop using Amazon Textract and Amazon Augmented AI

Businesses across many industries, including financial, medical, legal, and real estate, process a large number of documents for different business operations. Healthcare and life science organizations, for example, need to access data within medical records and forms to fulfill medical claims and streamline administrative processes. Amazon Textract is a machine learning (ML) service that makes […]

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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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