AWS Machine Learning Blog
Bringing real-time machine learning-powered insights to rugby using Amazon SageMaker
The Guinness Six Nations Championship began in 1883 as the Home Nations Championship among England, Ireland, Scotland, and Wales, with the inclusion of France in 1910 and Italy in 2000. It is among the oldest surviving rugby traditions and one of the best-attended sporting events in the world. The COVID-19 outbreak disrupted the end of […]
Building an NLU-powered search application with Amazon SageMaker and the Amazon OpenSearch Service KNN feature
September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. This post has also been updated with changes required for SageMaker SDK v2 and an improved notebook experience. The rise of semantic search engines has made ecommerce and retail businesses search easier for its consumers. Search engines powered by natural […]
Arcanum makes Hungarian heritage accessible with Amazon Rekognition
Arcanum specializes in digitizing Hungarian language content, including newspapers, books, maps, and art. With over 30 years of experience, Arcanum serves more than 30,000 global subscribers with access to Hungarian culture, history, and heritage. Amazon Rekognition Solutions Architects worked with Arcanum to add highly scalable image analysis to Arcanum Digitheca, a free service provided by […]
Securing Amazon SageMaker Studio connectivity using a private VPC
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 Amazon SageMaker Studio Notebooks for exploring datasets and building models. With the new ability to launch Amazon SageMaker Studio in your Amazon Virtual Private Cloud (Amazon VPC), you […]
Using Amazon SageMaker inference pipelines with multi-model endpoints
Businesses are increasingly deploying multiple machine learning (ML) models to serve precise and accurate predictions to their consumers. Consider a media company that wants to provide recommendations to its subscribers. The company may want to employ different custom models for recommending different categories of products—such as movies, books, music, and articles. If the company wants […]
Time series forecasting using unstructured data with Amazon Forecast and the Amazon SageMaker Neural Topic Model
As the volume of unstructured data such as text and voice continues to grow, businesses are increasingly looking for ways to incorporate this data into their time series predictive modeling workflows. One example use case is transcribing calls from call centers to forecast call handle times and improve call volume forecasting. In the retail or […]
Performing batch fraud predictions using Amazon Fraud Detector, Amazon S3, and AWS Lambda
Amazon Fraud Detector is a fully managed service that makes it easy to identify potentially fraudulent online activities, such as the creation of fake accounts or online payment fraud. Unlike general-purpose machine learning (ML) packages, Amazon Fraud Detector is designed specifically to detect fraud. Amazon Fraud Detector combines your data, the latest in ML science, […]
Automatically detecting personal protective equipment on persons in images using Amazon Rekognition
Workplace safety hazards can exist in many different forms: sharp edges, falling objects, flying sparks, chemicals, noise, and a myriad of other potentially dangerous situations. Safety regulators such as Occupational Safety and Health Administration (OSHA) and European Commission often require that businesses protect their employees and customers from hazards that can cause injury by providing […]
Detecting playful animal behavior in videos using Amazon Rekognition Custom Labels
Historically, humans have observed animal behaviors and applied them for different purposes. For example, behavioral observation is important in animal ecology, such as how often the behaviors are, when the behaviors occur, or whether there is individual difference or not. However, identifying and monitoring these behaviors and movements can be hard and can take a […]
Processing auto insurance claims at scale using Amazon Rekognition Custom Labels and Amazon SageMaker Ground Truth
Computer vision uses machine learning (ML) to build applications that process images or videos. With Amazon Rekognition, you can use pre-trained computer vision models to identify objects, people, text, activities, or inappropriate content. Our customers have use cases that span every industry, including media, finance, manufacturing, sports, and technology. Some of these use cases require […]