AWS Machine Learning Blog

Category: Artificial Intelligence

Graph-based recommendation system with Neptune ML: An illustration on social network link prediction challenges

Recommendation systems are one of the most widely adopted machine learning (ML) technologies in real-world applications, ranging from social networks to ecommerce platforms. Users of many online systems rely on recommendation systems to make new friendships, discover new music according to suggested music lists, or even make ecommerce purchase decisions based on the recommended products. […]

Secure access to Amazon SageMaker Studio with AWS SSO and a SAML application

Cloud security at AWS is the highest priority. Amazon SageMaker Studio offers various mechanisms to protect your data and code using integration with AWS security services like AWS Identity and Access Management (IAM), AWS Key Management Service (AWS KMS), or network isolation with Amazon Virtual Private Cloud (Amazon VPC). Customers in highly regulated industries, like […]

Industrial automation at Tyson with computer vision, AWS Panorama, and Amazon SageMaker

This is the first in a two-part blog series on how Tyson Foods, Inc., is utilizing machine learning to automate industrial processes at their meat packing plants by bringing the benefits of artificial intelligence applications at the edge. In part one, we discuss an inventory counting application for packaging lines built using Amazon SageMaker and […]

Develop an automatic review image inspection service with Amazon SageMaker

This is a guest post by Jihye Park, a Data Scientist at MUSINSA.  MUSINSA is one of the largest online fashion platforms in South Korea, serving 8.4M customers and selling 6,000 fashion brands. Our monthly user traffic reaches 4M, and over 90% of our demographics consist of teens and young adults who are sensitive to […]

How ReliaQuest uses Amazon SageMaker to accelerate its AI innovation by 35x 

Cybersecurity continues to be a top concern for enterprises. Yet the constantly evolving threat landscape that they face makes it harder than ever to be confident in their cybersecurity protections.

To address this, ReliaQuest built GreyMatter, an Open XDR-as-a-Service platform that brings together telemetry from any security and business solution, whether on-premises or in one or multiple clouds, to unify detection, investigation, response, and resilience.

In 2021, ReliaQuest turned to AWS to help it enhance its artificial intelligence (AI) capabilities and build new features faster.

Blur faces in videos automatically with Amazon Rekognition Video

With the advent of artificial intelligence (AI) and machine learning (ML), customers and the general public have become increasingly aware of their privacy, as well as the value that it holds in today’s data-driven world. Enterprises are actively seeking out and marketing privacy-first solutions, especially in the Computer Vision (CV) domain. They need to reassure […]

How Wix empowers customer care with AI capabilities using Amazon Transcribe

With over 200 million users worldwide, Wix is a leading cloud-based development platform for building fully personalized, high-quality websites. Wix makes it easy for anyone to create a beautiful and professional web presence. When Wix started, it was easy to understand user sentiment and identify product improvement opportunities because the user base was small. Such […]

How to approach conversation design with Amazon Lex: Building and testing (Part 3)

In parts one and two of our guide to conversation design with Amazon Lex, we discussed how to gather requirements for your conversational AI application and draft conversational flows. In this post, we help you bring all the pieces together. You’ll learn how draft an interaction model to deliver natural conversational experiences, and how to […]

Deploying ML models using SageMaker Serverless Inference

Amazon SageMaker Serverless Inference was recently announced at re:Invent 2021 as a new model hosting feature that lets customers serve model predictions without having to explicitly provision compute instances or configure scaling policies to handle traffic variations. Serverless Inference is a new deployment capability that complements SageMaker’s existing options for deployment that include: SageMaker Real-Time […]

Build and visualize a real-time fraud prevention system using Amazon Fraud Detector

October 2023: This post was reviewed and updated with an updated AWS CloudFormation template. August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. We’re living in a world of everything-as-an-online-service. Service providers from almost every industry […]