Category: Artificial Intelligence
Twin Neural Network Training with PyTorch and Fast.ai and its Deployment with TorchServe on Amazon SageMaker
In this post we demonstrate how to train a Twin Neural Network based on PyTorch and Fast.ai, and deploy it with TorchServe on Amazon SageMaker inference endpoint. For demonstration purposes, we build an interactive web application for users to upload images and make inferences from the trained and deployed model, based on Streamlit, which is an open source framework for data scientists to efficiently create interactive web-based data applications in pure Python.
Learn how AWS contributes to the scalability and operational efficiency of open source Ray and how AWS customers use Ray with AWS-managed services for secure, scalable, and enterprise-ready workloads across the entire data processing and AI/ML pipeline.
Learn how to use the open source Python SDK for Lookout for Vision in either AWS Glue or AWS Lambda to quickly identify differences in images of objects at scale.
This post was contributed by Thomas Ngue Minkeng, Nathalie Au, Marc Bouffard, and Pierre-Marie Airiau from Ogury Ogury, the Personified Advertising company, is using open source machine learning (ML) on AWS to deliver a planned 300,000 inferences per second under 10-ms latency. Ogury’s breakthrough advertising engine delivers precision, sustainability, and privacy protection within one technology […]
Amazon CloudWatch is now available for Ray on Amazon Elastic Compute Cloud (Amazon EC2). Ray is an open source (Apache 2.0 License) framework to build and scale distributed applications. CloudWatch is a monitoring and observability service that provides data and actionable insights to monitor your applications, respond to system-wide performance changes, and optimize resource utilization. […]
Companies providing digital services are looking for ways to effectively identify fraudulent activities, such as online payment fraud and fake account creation. Amazon Fraud Detector is a fully managed service that uses machine learning (ML) and builds on 20 years of fraud detection expertise from Amazon Web Services (AWS) and Amazon.com to automatically identify potentially […]
GraphQL is an application-level query language that helps clients and servers communicate by establishing a common protocol for queries. It represents an alternative to the REST style: unlike REST, GraphQL gives the client, not the server, the power to define what kind of data will be included in the response to its query. GraphQL allows […]
This post was written by Frank Munz, Staff Developer Advocate at Databricks. An introduction to Delta Sharing During the past decade, much thought went into system and application architectures using domain-driven design and microservices, but we are still on the verge of building distributed data meshes. Such data meshes are based on two fundamental principles: […]
Modern data science environments often involve many independent projects, each spanning multiple accounts. In order to maintain a global overview of the activities within the projects, a mechanism to collect data from the different accounts into a central one is crucial. In this post, we show how to leverage existing services—Amazon DynamoDB, AWS Lambda, Amazon […]
This post was written by Willem Pienaar, Principal Engineer at Tecton and creator of Feast. Feast is an open source feature store and a fast, convenient way to serve machine learning (ML) features for training and online inference. Feast lets you build point-in-time correct training datasets from feature data, allows you to deploy a production-grade […]