AWS Machine Learning Blog

Category: Amazon Comprehend

Amazon Comprehend document classifier adds layout support for higher accuracy

The ability to effectively handle and process enormous amounts of documents has become essential for enterprises in the modern world. Due to the continuous influx of information that all enterprises deal with, manually classifying documents is no longer a viable option. Document classification models can automate the procedure and help organizations save time and resources. […]

Build end-to-end document processing pipelines with Amazon Textract IDP CDK Constructs

September 2023: This post was reviewed and updated. Intelligent document processing (IDP) with AWS helps automate information extraction from documents of different types and formats, quickly and with high accuracy, without the need for machine learning (ML) skills. Faster information extraction with high accuracy can help you make quality business decisions on time, while reducing […]

How the UNDP Independent Evaluation Office is using AWS AI/ML services to enhance the use of evaluation to support progress toward the Sustainable Development Goals

The United Nations (UN) was founded in 1945 by 51 original Member States committed to maintaining international peace and security, developing friendly relations among nations, and promoting social progress, better living standards, and human rights. The UN is currently made up of 193 Member States and has evolved over the years to keep pace with […]

Simplify continuous learning of Amazon Comprehend custom models using Comprehend flywheel

Amazon Comprehend is a managed AI service that uses natural language processing (NLP) with ready-made intelligence to extract insights about the content of documents. It develops insights by recognizing the entities, key phrases, language, sentiments, and other common elements in a document. The ability to train custom models through the Custom classification and Custom entity […]

Introducing the Amazon Comprehend flywheel for MLOps

The world we live in is rapidly changing, and so are the data and features that companies and customers use to train their models. Retraining models to keep them in sync with these changes is critical to maintain accuracy. Therefore, you need an agile and dynamic approach to keep models up to date and adapt […]

Redacting PII data at The Very Group with Amazon Comprehend

This is guest post by Andy Whittle, Principal Platform Engineer – Application & Reliability Frameworks at The Very Group. At The Very Group, which operates digital retailer Very, security is a top priority in handling data for millions of customers. Part of how The Very Group secures and tracks business operations is through activity logging […]

How to redact PII data in conversation transcripts

Customer service interactions often contain personally identifiable information (PII) such as names, phone numbers, and dates of birth. As organizations incorporate machine learning (ML) and analytics into their applications, using this data can provide insights on how to create more seamless customer experiences. However, the presence of PII information often restricts the use of this […]

Amazon SageMaker JumpStart now offers Amazon Comprehend notebooks for custom classification and custom entity detection

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning (ML) to discover insights from text. Amazon Comprehend provides customized features, custom entity recognition, custom classification, and pre-trained APIs such as key phrase extraction, sentiment analysis, entity recognition, and more so you can easily integrate NLP into your applications. We recently added […]

Introducing one-step classification and entity recognition with Amazon Comprehend for intelligent document processing

“Intelligent document processing (IDP) solutions extract data to support automation of high-volume, repetitive document processing tasks and for analysis and insight. IDP uses natural language technologies and computer vision to extract data from structured and unstructured content, especially from documents, to support automation and augmentation.”  – Gartner The goal of Amazon’s intelligent document processing (IDP) […]

Real-time analysis of customer sentiment using AWS

Companies that sell products or services online need to constantly monitor customer reviews left on their website after purchasing a product. The company’s marketing and customer service departments analyze these reviews to understand customer sentiment. For example, marketing could use this data to create campaigns targeting different customer segments. Customer service departments could use this […]