AWS Machine Learning Blog

Category: Artificial Intelligence

Build a solution for a computer vision skin lesion classifier using Amazon SageMaker Pipelines

Amazon SageMaker Pipelines is a continuous integration and continuous delivery (CI/CD) service designed for machine learning (ML) use cases. You can use it to create, automate, and manage end-to-end ML workflows. It tackles the challenge of orchestrating each step of an ML process, which requires time, effort, and resources. To facilitate its use, multiple templates […]

How Amazon Search runs large-scale, resilient machine learning projects with Amazon SageMaker

If you have searched for an item to buy on amazon.com, you have used Amazon Search services. At Amazon Search, we’re responsible for the search and discovery experience for our customers worldwide. In the background, we index our worldwide catalog of products, deploy highly scalable AWS fleets, and use advanced machine learning (ML) to match […]

Customize business rules for intelligent document processing with human review and BI visualization

A massive amount of business documents are processed daily across industries. Many of these documents are paper-based, scanned into your system as images, or in an unstructured format like PDF. Each company may apply unique rules associated with its business background while processing these documents. How to extract information accurately and process them flexibly is […]

Automate classification of IT service requests with an Amazon Comprehend custom classifier

Enterprises often deal with large volumes of IT service requests. Traditionally, the burden is put on the requester to choose the correct category for every issue. A manual error or misclassification of a ticket usually means a delay in resolving the IT service request. This can result in reduced productivity, a decrease in customer satisfaction, […]

Detect fraud in mobile-oriented businesses using GrabDefence device intelligence and Amazon Fraud Detector

In this post, we present a solution that combines rich mobile device intelligence with customized machine learning (ML) modeling to help you catch fraudsters who exploit mobile apps. GrabDefence (GD), Grab’s proprietary fraud detection and prevention technology, and AWS have launched GDxAFD, a fraud detection solution tailored for mobile apps that integrates GD’s device intelligence […]

How Synamedia uses Amazon Rekognition Video to build advanced video search capabilities for long-form video

Synamedia is a leading video technology provider addressing the needs for premium video service providers and direct-to-consumer (D2C) with a comprehensive solution portfolio. Synamedia solutions spread across several pillars such as video networks, TV platforms, advertisement and monetization, and content protection and piracy disruption. Synamedia partnered with AWS to use artificial intelligence (AI) to develop […]

Increase ML model performance and reduce training time using Amazon SageMaker built-in algorithms with pre-trained models

Model training forms the core of any machine learning (ML) project, and having a trained ML model is essential to adding intelligence to a modern application. A performant model is the output of a rigorous and diligent data science methodology. Not implementing a proper model training process can lead to high infrastructure and personnel costs […]

InformedIQ automates verifications for Origence’s auto lending using machine learning

This post was co-written with Robert Berger and Adine Deford from InformedIQ. InformedIQ is the leader in AI-based software used by the nation’s largest financial institutions to automate loan processing verifications and consumer credit applications in real time per the lenders’ policies. They improve regulatory compliance, reduce cost, and increase accuracy by decreasing human error […]

Prevent account takeover at login with the new Account Takeover Insights model in Amazon Fraud Detector

Digital is the new normal, and there’s no going back. Every year, consumers visit, on average, 191 websites or services requiring a user name and password, and the digital footprint is expected to grow exponentially. So much exposure naturally brings added risks like account takeover (ATO). Each year, bad actors compromise billions of accounts through […]

Metrics for evaluating content moderation in Amazon Rekognition and other content moderation services

Content moderation is the process of screening and monitoring user-generated content online. To provide a safe environment for both users and brands, platforms must moderate content to ensure that it falls within preestablished guidelines of acceptable behavior that are specific to the platform and its audience. When a platform moderates content, acceptable user-generated content (UGC) […]