AWS Machine Learning Blog

Category: AWS Lambda

Simplify and automate anomaly detection in streaming data with Amazon Lookout for Metrics

Do you want to monitor your business metrics and detect anomalies in your existing streaming data pipelines? Amazon Lookout for Metrics is a service that uses machine learning (ML) to detect anomalies in your time series data. The service goes beyond simple anomaly detection. It allows developers to set up autonomous monitoring for important metrics […]

Event-based fraud detection with direct customer calls using Amazon Connect

Several recent surveys show that more than 80% of consumers prefer spending with a credit card over cash. Thanks to advances in AI and machine learning (ML), credit card fraud can be detected quickly, which makes credit cards one of the safest and easiest payment methods to use. The challenge with cards, however, is that […]

Annotate DICOM images and build an ML model using the MONAI framework on Amazon SageMaker

DICOM (Digital Imaging and Communications in Medicine) is an image format that contains visualizations of X-Rays and MRIs as well as any associated metadata. DICOM is the standard for medical professionals and healthcare researchers for visualizing and interpreting X-Rays and MRIs. The purpose of this post is to solve two problems: Visualize and label DICOM […]

Build reusable, serverless inference functions for your Amazon SageMaker models using AWS Lambda layers and containers

July 2023: This post was reviewed for accuracy. Please refer to Deploying ML models using SageMaker Serverless Inference, a new inference option that enables you to easily deploy machine learning models for inference without having to configure or manage the underlying infrastructure. In AWS, you can host a trained model multiple ways, such as via […]

Create a serverless pipeline to translate large documents with Amazon Translate

In our previous post, we described how to translate documents using the real-time translation API from Amazon Translate and AWS Lambda. However, this method may not work for files that are too large. They may take too much time, triggering the 15-minute timeout limit of Lambda functions. One can use batch API, but this is available only in seven AWS Regions (as […]

Automatically scale Amazon Kendra query capacity units with Amazon EventBridge and AWS Lambda

Data is proliferating inside the enterprise and employees are using more applications than ever before to get their jobs done, in fact according to Okta Inc., the number of software apps deployed by large firms across all industries world-wide has increased 68%, reaching an average of 129 apps per company. As employees continue to self-serve […]

Segment paragraphs and detect insights with Amazon Textract and Amazon Comprehend

Many companies extract data from scanned documents containing tables and forms, such as PDFs. Some examples are audit documents, tax documents, whitepapers, or customer review documents. For customer reviews, you might be extracting text such as product reviews, movie reviews, or feedback. Further understanding of the individual and overall sentiment of the user base from […]

Scale session-aware real-time product recommendations on Shopify with Amazon Personalize and Amazon EventBridge

January 2022 – HiConversion is now Obviyo. We have updated this blog to reflect the new company name. You can read more about the name change on Obviyo’s blog. This is a guest post by Jeff McKelvey, Principal Development Lead at Obviyo. The team at Obviyo has collaborated closely with James Jory, Applied AI Services […]

Intelligent governance of document processing pipelines for regulated industries

Processing large documents like PDFs and static images is a cornerstone of today’s highly regulated industries. From healthcare information like doctor-patient visits and bills of health, to financial documents like loan applications, tax filings, research reports, and regulatory filings, these documents are integral to how these industries conduct business. The mechanisms by which these documents […]

Build a CI/CD pipeline for deploying custom machine learning models using AWS services

Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the ML process to make it easier to develop high-quality ML artifacts. AWS Serverless Application Model (AWS SAM) is […]