AWS Machine Learning Blog

Getting started with the Amazon Kendra SharePoint Online connector

Amazon Kendra is a highly accurate and easy-to-use enterprise search service powered by machine learning (ML). To get started with Amazon Kendra, we offer data source connectors to get your documents easily ingested and indexed. This post describes how to use Amazon Kendra’s SharePoint Online connector. To allow the connector to access your SharePoint Online […]

Learn from the first place winner of the first AWS DeepComposer Chartbusters Bach to the Future Challenge

AWS is excited to announce the winner of the first AWS DeepComposer Chartbusters Challenge, Catherine Chui. AWS DeepComposer gives developers a creative way to get started with machine learning (ML). To make the learning more fun, in June 2020 we launched the Chartbusters Challenge, a competition where developers use AWS DeepComposer to create original compositions […]

Building a customized recommender system in Amazon SageMaker

Recommender systems help you tailor customer experiences on online platforms. Amazon Personalize is an artificial intelligence and machine learning service that specializes in developing recommender system solutions. It automatically examines the data, performs feature and algorithm selection, optimizes the model based on your data, and deploys and hosts the model for real-time recommendation inference. However, […]

Relevance tuning with Amazon Kendra

Amazon Kendra is a highly accurate and easy-to-use enterprise search service powered by machine learning (ML). As your users begin to perform searches using Amazon Kendra, you can fine-tune which search results they receive. For example, you might want to prioritize results from certain data sources that are more actively curated and therefore more authoritative. […]

Using A/B testing to measure the efficacy of recommendations generated by Amazon Personalize

Machine learning (ML)-based recommender systems aren’t a new concept, but developing such a system can be a resource-intensive task—from data management during training and inference, to managing scalable real-time ML-based API endpoints. Amazon Personalize allows you to easily add sophisticated personalization capabilities to your applications by using the same ML technology used on for […]

The fastest driver in Formula 1

This blog post was co-authored, and includes an introduction, by Rob Smedley, Director of Data Systems at Formula 1 Formula 1 (F1) racing is the most complex sport in the world. It is the blended perfection of human and machine that create the winning formula. It is this blend that makes F1 racing, or more […]

Amazon Personalize can now create up to 50% better recommendations for fast changing catalogs of new products and fresh content

This blog post was last reviewed or updated April, 2022 with database schema updates. Amazon Personalize now makes it easier to create personalized recommendations for fast-changing catalogs of books, movies, music, news articles, and more, improving recommendations by up to 50% (measured by click-through rate) with just a few clicks in the AWS console. Without […]

How Citibot’s chatbot search engine uses AI to find more answers

Citibot is a technology company that builds AI-powered chat solutions for local governments such as Fort Worth, Texas; Charleston, South Carolina; and Arlington, Virginia. With Citibot, local residents can quickly get answers to city-related questions, report issues, and receive real-time alerts via text responses. To power these interactions, Citibot uses Amazon Lex, a service for building conversational interfaces for text and voice applications. Citibot built the chatbot to handle basic call queries, which allows government employees to allocate more time to higher-impact community actions.