AWS Machine Learning Blog

Amazon Polly adds Arabic language support

On April 17th, 2019 Amazon Polly launched an Arabic female text-to-speech (TTS) voice called Zeina. This voice is clear and natural-sounding. The voice masters tongue twisters, and it can whisper, just like all other Amazon Polly products. Let’s hear Zeina introduce herself: Listen now Voiced by Amazon Polly Hello, my name is Zeina, I am the […]

Your guide to Amazon re:MARS: Jeff Bezos, Andrew Ng, Robert Downey Jr. and more…  

The inaugural Amazon re:MARS event pairs the best of what’s possible today with perspectives on the future of machine learning, automation, robotics, and space travel. Based on the exclusive MARS event founded by Jeff Bezos, Amazon re:MARS brings together the world of business and technology in a premier thought-leadership event. With more than 100 sessions, […]

Developer at the AWS DeepRacer League Singapore race sets new world record lap time

The AWS DeepRacer League, the world’s first autonomous racing league open to developers of all skill levels held a race in Singapore this week (April 10-11). This was the third of twenty races on the worldwide Summit Circuit.  Following the first two races in Santa Clara, California and Paris, France, excitement was building to see […]

Protagonist adopts Amazon Translate to expand analytics to multilingual content

This is a guest blog post by Bryan Pelley, COO of Protagonist. Protagonist, in their own words “helps organizations communicate more effectively through a data-driven understanding of public discourse.” Protagonist is a pioneer of the art and science of understanding narratives. We define narratives as the beliefs that an audience holds that are  composed of […]

Extending Amazon SageMaker factorization machines algorithm to predict top x recommendations

Amazon SageMaker gives you the flexibility that you need to address sophisticated business problems with your machine learning workloads. Built-in algorithms help you get started quickly.  In this blog post we’ll outline how you can extend the built-in factorization machines algorithm to predict top x recommendations. This approach is ideal when you want to generate […]

Amazon Comprehend now supports resource tagging for custom models

Amazon Comprehend customers are solving a variety of use cases with custom classification and entity type models. For example, customers are building classifiers to organize their daily customer feedback into categories like “loyalty,” “sales,” or “product defect.” Custom entity models enable customers to analyze text for their own terms and phrases, such as product IDs […]

Amazon SageMaker automatic model tuning now supports random search and hyperparameter scaling

We are excited to introduce two highly requested features to automatic model tuning in Amazon SageMaker: random search and hyperparameter scaling. This post describes these features, explains when and how to enable them, and shows how they can improve your search for hyperparameters that perform well. If you are in a hurry, you’ll be happy […]

Amazon Comprehend now support KMS encryption

Amazon Comprehend is a fully managed natural language processing (NLP) service that enables text analytics for important workloads. For example, analyzing market research reports for key market indicators or data that contains PII information. Customers that work with highly sensitive, encrypted data can now easily enable Comprehend to work with this encrypted data via an integration […]

AWS DeepRacer League hits the road for more fun and excitement for developers!

From developer to machine learning developer The AWS DeepRacer League is the world’s first autonomous racing league open to developers of all skill levels and it kicked off last week in Santa Clara, California. Chris Miller was crowned our first champion of the 2019 season. Chris is the founder of Cloud Brigade, based in Santa Cruz, […]

Create high-quality instructions for Amazon SageMaker Ground Truth labeling jobs

Amazon SageMaker Ground Truth helps you quickly build highly accurate training datasets for machine learning (ML). You can use your own workers, a choice of vendor-managed workforces that specialize in data labeling, or a public workforce powered by Amazon Mechanical Turk to provide the human-generated labels. To get high-quality labels, you must provide simple, concise, […]