AWS Machine Learning Blog

Category: Artificial Intelligence

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 […]

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Automatically extract text and structured data from documents with Amazon Textract

Documents are a primary tool for record keeping, communication, collaboration, and transactions across many industries, including financial, medical, legal, and real estate. The millions of mortgage applications and hundreds of millions of W2 tax forms processed each year are just a few examples of such documents. A lot of information is locked in unstructured documents. […]

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Powering a search engine with Amazon SageMaker

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 smartphone app. The company partners with leading brands and retailers to offer offers on groceries, […]

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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 […]

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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 […]

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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 […]

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

Updated 10/4/2019 to fix dependency and version issues with Amazon SageMaker and fixed delimiter issues when preparing scripts. Machine learning (ML) workflows orchestrate and automate sequences of ML tasks by enabling data collection and transformation. This is followed by training, testing, and evaluating a ML model to achieve an outcome. For example, you might want […]

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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 […]

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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 […]

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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 […]

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