AWS Machine Learning

The University of Maryland, Baltimore County’s Bina lab is a multidisciplinary research lab for employing advanced computer vision, machine learning (ML), and remote sensing techniques to discover new knowledge o […]

Today, we’re excited to announce a new similar items recommendation recipe (aws-similar-items) in Amazon Personalize that helps you leverage your users’ interaction histories and what you know about the items in […]

When companies deal with data that comes from various sources or the collection of this data has changed over time, the data often becomes difficult to organize. Perhaps you have product category names that are […]

New trends are shaping the credit card industry as shopping habits have rapidly evolved over the last 18 months. The pandemic has accelerated the move away from cash towards cards. Card issuers are transforming […]

As you plan your new Amazon Lex application, the following conversation design best practices can help your team succeed in creating a great customer experience. In our previous post, we discussed how to create […]

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at any scale. Typically, you can use the […]

The ability to predict that a particular customer is at a high risk of churning, while there is still time to do something about it, represents a huge potential revenue source for every online business. Depending […]

Fraud teams need a secure, fast, and flexible transaction fraud detection solution to combat global fraudsters. Unlike many solutions on the market, Amazon Fraud Detector allows you to tailor your fraud detection […]

In Part 1 of this series, we showed how to build a brand detection solution using Amazon SageMaker Ground Truth and Amazon Rekognition Custom Labels. The solution was built on a serverless architecture with a […]

AWS customers are increasingly using computer vision (CV) models on large input payloads that can take a few minutes of processing time. For example, space technology companies work with a stream of […]

From application forms, to identity documents, recent utility bills, and bank statements, many business processes today still rely on exchanging and analyzing human-readable documents—particularly in industries l […]

A continuous integration and continuous delivery (CI/CD) pipeline helps you automate steps in your machine learning (ML) applications such as data ingestion, data preparation, feature engineering, modeling […]

Social media platforms provide a channel of communication for consumers to talk about various products, including the medications they take. For pharmaceutical companies, monitoring and effectively tracking […]

According to a recent study, defective products cost industries over $2 billion from 2012–2017. Defect detection within manufacturing is an important business use case, especially in high-value product i […]

You may have tables in your Amazon Redshift data warehouse or in your Amazon Simple Storage Service (Amazon S3) data lake full of records containing customer case notes, product reviews, and social media messages, […]

Starting today, we’re releasing new tools for multimodal financial analysis within Amazon SageMaker JumpStart. SageMaker JumpStart helps you quickly and easily get started with machine learning (ML) and provides a […]

Starting today, we’re releasing new tools for multimodal financial analysis within Amazon SageMaker JumpStart. SageMaker JumpStart helps you quickly and easily get started with machine learning (ML). It provides a […]

Amazon SageMaker projects are AWS Service Catalog provisioned products that enable you to easily create end-to-end machine learning (ML) solutions. SageMaker projects give organizations the ability to use […]

More customers are finding the need to build larger, scalable, and more cost-effective machine learning (ML) inference pipelines in the cloud. Outside of these base prerequisites, the requirements of ML inference […]

You can deploy machine learning (ML) models for real-time inference with large libraries or pre-trained models. Common use cases include sentiment analysis, image classification, and search applications. These ML […]