AWS Machine Learning Blog

Category: Advanced (300)

Deploy large language models on AWS Inferentia2 using large model inference containers

You don’t have to be an expert in machine learning (ML) to appreciate the value of large language models (LLMs). Better search results, image recognition for the visually impaired, creating novel designs from text, and intelligent chatbots are just some examples of how these models are facilitating various applications and tasks. ML practitioners keep improving […]

Deploy pre-trained models on AWS Wavelength with 5G edge using Amazon SageMaker JumpStart

With the advent of high-speed 5G mobile networks, enterprises are more easily positioned than ever with the opportunity to harness the convergence of telecommunications networks and the cloud. As one of the most prominent use cases to date, machine learning (ML) at the edge has allowed enterprises to deploy ML models closer to their end-customers […]

Solution Diagram

Implement unified text and image search with a CLIP model using Amazon SageMaker and Amazon OpenSearch Service

The rise of text and semantic search engines has made ecommerce and retail businesses search easier for its consumers. Search engines powered by unified text and image can provide extra flexibility in search solutions. You can use both text and images as queries. For example, you have a folder of hundreds of family pictures in […]

Snapper provides machine learning-assisted labeling for pixel-perfect image object detection

Bounding box annotation is a time-consuming and tedious task that requires annotators to create annotations that tightly fit an object’s boundaries. Bounding box annotation tasks, for example, require annotators to ensure that all edges of an annotated object are enclosed in the annotation. In practice, creating annotations that are precise and well-aligned to object edges […]

Recommend top trending items to your users using the new Amazon Personalize recipe

Amazon Personalize is excited to announce the new Trending-Now recipe to help you recommend items gaining popularity at the fastest pace among your users. Amazon Personalize is a fully managed machine learning (ML) service that makes it easy for developers to deliver personalized experiences to their users. It enables you to improve customer engagement by […]

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

This is joint post co-written by Leidos and AWS. Leidos is a FORTUNE 500 science and technology solutions leader working to address some of the world’s toughest challenges in the defense, intelligence, homeland security, civil, and healthcare markets. Leidos has partnered with AWS to develop an approach to privacy-preserving, confidential machine learning (ML) modeling where […]

Build a machine learning model to predict student performance using Amazon SageMaker Canvas

There has been a paradigm change in the mindshare of education customers who are now willing to explore new technologies and analytics. Universities and other higher learning institutions have collected massive amounts of data over the years, and now they are exploring options to use that data for deeper insights and better educational outcomes. You […]

Access Snowflake data using OAuth-based authentication in Amazon SageMaker Data Wrangler

In this post, we show how to configure a new OAuth-based authentication feature for using Snowflake in Amazon SageMaker Data Wrangler. Snowflake is a cloud data platform that provides data solutions for data warehousing to data science. Snowflake is an AWS Partner with multiple AWS accreditations, including AWS competencies in machine learning (ML), retail, and […]

Remote monitoring of raw material supply chains for sustainability with Amazon SageMaker geospatial capabilities

Deforestation is a major concern in many tropical geographies where local rainforests are at severe risk of destruction. About 17% of the Amazon rainforest has been destroyed over the past 50 years, and some tropical ecosystems are approaching a tipping point beyond which recovery is unlikely. A key driver for deforestation is raw material extraction […]

Best practices for viewing and querying Amazon SageMaker service quota usage

Amazon SageMaker customers can view and manage their quota limits through Service Quotas. In addition, they can view near real-time utilization metrics and create Amazon CloudWatch metrics to view and programmatically query SageMaker quotas. SageMaker helps you build, train, and deploy machine learning (ML) models with ease. To learn more, refer to Getting started with […]