AWS Machine Learning Blog

By providing a scalable cloud platform for building communications experiences, Twilio enables developers and businesses to build any customer engagement into their applications using simple and powerful APIs for voice, messaging, and video. Businesses like Morgan Stanley, Marks & Spencer, Netflix, Lyft, Airbnb, and more than 50,000 others are modernizing the way they communicate with […]

Thorn is a non-profit organization dedicated to stopping the spread of child sexual abuse material and standing up to child traffickers. Thorn’s tools have been used to identify 5,894 child sex trafficking victims and rescue 103 children where their sexual abuse was recorded and distributed. Using AWS services such as Amazon Rekognition, Thorn has seen […]

Not only does Amazon SageMaker  provide easy scalability and distribution to train and host ML models, it is modularized so that the process of training a model is decoupled from deploying the model. This means that models that are trained outside of Amazon SageMaker can be brought into SageMaker only to be deployed. This is very useful […]

Supervised learning needs labels, or annotations, that tell the algorithm what the right answers are in the training phases of your project. In fact, many of the examples of using MXNet, TensorFlow, and PyTorch start with annotated data sets you can use to explore the various features of those frameworks. Unfortunately, when you move from […]

Amazon Polly is an AWS service that turns text into lifelike speech. We’re excited to announce new Hindi language support and the release of our first bilingual voice. Aditi is a female voice that speaks Hindi and Indian English fluently. Let’s hear Aditi introduce herself in both Indian English and Hindi. Listen to the Hindi […]

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. See details. People spend a lot of time searching documents. First you go to your document store and then you search for relevant documents. If you’re looking for a text inside the document, then you need to do another search. In this […]

Data scientists and developers can use the Amazon SageMaker fully managed machine learning service to build and train machine learning (ML) models, and then directly deploy them into a production-ready hosted environment. In this blog post we’ll show you  how to use Amazon SageMaker to do transfer learning using a TensorFlow container with our own […]

This blog shares some brief thoughts on machine learning accuracy and bias. Let’s start with some comments about a recent ACLU blog in which they ran a facial recognition trial. Using Rekognition, the ACLU built a face database using 25,000 publicly available arrest photos and then performed facial similarity searches on that database using public […]

The AWS Deep Learning AMIs (DLAMI) for Ubuntu and Amazon Linux are now pre-installed and fully configured with Open Neural Network Exchange (ONNX), enabling model portability across deep learning frameworks. In this blog post we’ll introduce ONNX, and demonstrate how ONNX can be used on the DLAMI to port models across frameworks. What is ONNX? ONNX is an open […]

April 2023 Update: Starting January 31, 2024, you will no longer be able to access AWS DeepLens through the AWS management console, manage DeepLens devices, or access any projects you have created. To learn more, refer to these frequently asked questions about AWS DeepLens end of life. We announced the AWS DeepLens Inclusivity Challenge two weeks […]