AWS Machine Learning Blog

Capturing memories: GeoSnapShot uses Amazon Rekognition to identify athletes

If you’ve ever competed in a sporting event and painstakingly sifted through event photos to find yourself later, you’ll appreciate GeoSnapShot’s innovative solution powered by Amazon Rekognition. GeoSnapShot founder Andy Edwards was first introduced to the world of sports photography when he started accompanying his wife, a competitive equestrian, to her riding events and photographing […]

Automatically extract text and structured data from documents with Amazon Textract

September 2022: Post was reviewed for accuracy. December 2021: This post has been updated with the latest use cases and capabilities for Amazon Textract.  September 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. Documents are a primary tool for record keeping, communication, collaboration, and transactions across many industries, including financial, […]

Powering a search engine with Amazon SageMaker

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. This is a guest post by Evan Harris, Manager of Machine Learning at Ibotta. In their own words, “Ibotta is transforming the shopping experience by making it easy for consumers to earn cash back on everyday purchases through a single […]

Racing tips from AWS DeepRacer League winners in Stockholm, and AWS DeepRacer TV!

The AWS DeepRacer League is the world’s first global autonomous racing league. There are races at 21 AWS Summits globally and select Amazon events, as well as monthly virtual races happening online and open for racing. No matter where you are in the world or your skill level, you can join the league. Get a […]

Exploring data warehouse tables with machine learning and Amazon SageMaker notebooks

Are you a data scientist with data warehouse tables that you’d like to explore in your machine learning (ML) environment? If so, read on. In this post, I show you how to perform exploratory analysis on large datasets stored in your data warehouse and cataloged in your AWS Glue Data Catalog from your Amazon SageMaker […]

The AWS DeepRacer League virtual circuit is underway—win a trip to re:Invent 2019!

The competition is heating up in the AWS DeepRacer League, the world’s first global autonomous racing league, open to anyone. The first round is almost halfway home, now that 9 of the 21 stops on the summit circuit schedule are complete. Developers continue to build new machine learning skills and post winning times to the […]

Build end-to-end machine learning workflows with Amazon SageMaker and Apache Airflow

October 2021: Updating for airflow versions with MWAA supported releases, simplifying dependencies and adding Aurora Serverless as a DB option. In addition, new features (Session Manager integration and CloudFormation Stack status for the EC2 deployment) have been added. Machine learning (ML) workflows orchestrate and automate sequences of ML tasks by enabling data collection and transformation. […]

More ways to compete and win in the AWS DeepRacer League and two new champions!

It’s been a busy week for the AWS DeepRacer League. The world’s first global autonomous racing league allows machine learning developers of all skill levels to get hands-on with machine learning in a fun and exciting way. On April 29 2019, the virtual circuit of the AWS DeepRacer League opened. The virtual circuit allows racers […]

Build a custom data labeling workflow with Amazon SageMaker Ground Truth

Good machine learning models are built with large volumes of high-quality training data. But creating this kind of training data is expensive, complicated, and time-consuming. To help a model learn how to make the right decisions, you typically need a human to manually label the training data. Amazon SageMaker Ground Truth provides labeling workflows for […]

Amazon SageMaker Object2Vec adds new features that support automatic negative sampling and speed up training

Today, we introduce four new features of Amazon SageMaker Object2Vec: negative sampling, sparse gradient update, weight-sharing, and comparator operator customization. Amazon SageMaker Object2Vec is a general-purpose neural embedding algorithm. If you’re unfamiliar with Object2Vec, see the blog post Introduction to Amazon SageMaker Object2Vec, which provides a high-level overview of the algorithm with links to four notebook […]