AWS Machine Learning Blog

Build conversational experiences for credit card services using Amazon Lex

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 their products to better serve cardmembers through innovations such as contactless payments and mobile wallet. The rapid change in consumer behavior […]

Detect online transaction fraud with new Amazon Fraud Detector features

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 efforts specifically to your data and business challenge while also bringing the latest in fraud detection machine learning (ML) technology to bear on […]

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Build, tune, and deploy an end-to-end churn prediction model using Amazon SageMaker Pipelines

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 on the industry and business objective, the problem statement can be multi-layered. The following are some business objectives based […]

Build your own brand detection and visibility using Amazon SageMaker Ground Truth and Amazon Rekognition Custom Labels – Part 2: Training and analysis workflows

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 custom user interface to identify a company brand or logo from video content and get an in-depth view of screen […]

Bring structure to diverse documents with Amazon Textract and transformer-based models on Amazon SageMaker

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 like financial services and law. In this post, we show how you can use Amazon SageMaker, an end-to-end platform for machine learning (ML), to automate especially challenging document analysis […]

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Run computer vision inference on large videos with Amazon SageMaker asynchronous endpoints

This blog post was last reviewed and updated August, 2022 with a generator-based approach for video payloads of longer duration. 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 high-resolution satellite imagery […]

Detect defects in automotive parts with Amazon Lookout for Vision and Amazon SageMaker

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 industries like the automotive industry. This allows for early diagnosis of anomalies to improve production line efficacy and product quality, and saves capital costs. Although advanced anomaly […]

Build a system for catching adverse events in real-time using Amazon SageMaker and Amazon QuickSight

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 product performance provides customer feedback about the product, which is vital to maintaining and improving patient safety. However, when an unexpected medical occurrence resulting from a pharmaceutical product […]

Create a cross-account machine learning training and deployment environment with AWS Code Pipeline

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 training, and model deployment. A pipeline across multiple AWS accounts improves security, agility, and resilience because an AWS account provides a natural security and access boundary for your […]

Translate, redact, and analyze text using SQL functions with Amazon Redshift, Amazon Translate, and Amazon Comprehend

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, in many languages. Your task is to identify the products that people are talking about, determine if they’re expressing happy thoughts […]