AWS Machine Learning Blog

Query drug adverse effects and recalls based on natural language using Amazon Comprehend Medical

In this post, we demonstrate how to use Amazon Comprehend Medical to extract medication names and medical conditions to monitor drug safety and adverse events. Amazon Comprehend Medical is a natural language processing (NLP) service that uses machine learning (ML) to easily extract relevant medical information from unstructured text. We query the OpenFDA API (an open-source API published by […]

Building a scalable outbound call engine using Amazon Connect and Amazon Lex

­ This is a guest post by AWS Machine Learning Hero Cyrus Wong. Staying connected with family, friends, and colleagues is easy for most people who live with or close to others. For educators who need to communicate lessons and schedules with their students, or businesses who communicate with new and existing customers, staying connected […]

Fine-tuning a PyTorch BERT model and deploying it with Amazon Elastic Inference on Amazon SageMaker

November 2022: The solution described here is not the latest best practice. The new HuggingFace Deep Learning Container (DLC) is available in Amazon SageMaker (see Use Hugging Face with Amazon SageMaker). For customer training BERT models, the recommended pattern is to use HuggingFace DLC, shown as in Finetuning Hugging Face DistilBERT with Amazon Reviews Polarity dataset. […]

Facebook uses Amazon EC2 to evaluate the Deepfake Detection Challenge

In October 2019, AWS announced that it was working with Facebook, Microsoft, and the Partnership on AI on the first Deepfake Detection Challenge. Deepfake algorithms are the same as the underlying technology that has given us realistic animation effects in movies and video games. Unfortunately, those same algorithms have been used by bad actors to […]

AWS DeepRacer Evo and Sensor Kit now available for purchase

AWS DeepRacer is a fully autonomous 1/18th scale race car powered by reinforcement learning (RL) that gives machine learning (ML) developers of all skill levels the opportunity to learn and build their ML skills in a fun and competitive way. AWS DeepRacer Evo includes new features and capabilities to help you learn more about ML […]

Detecting and analyzing incorrect model predictions with Amazon SageMaker Model Monitor and Debugger

Convolutional neural networks (CNNs) achieve state-of-the-art results in tasks such as image classification and object detection. They are used in many diverse applications, such as in autonomous driving to detect traffic signs and objects on the street, in healthcare to more accurately classify anomalies in image-based data, and in retail for inventory management. However, CNNs […]

Announcing the launch of Amazon Comprehend custom entity recognition real-time endpoints

Update Sep 28, 2020 – New features: Amazon Comprehend custom entity recognition real-time endpoints now supports application auto scaling. Please refer to the section Auto Scaling with real-time endpoints in this post to learn more. Update Aug 12, 2020 – New features: Amazon Comprehend adds five new languages(Spanish, French, German, Italian and Portuguese) read here. Amazon […]

Optimizing I/O for GPU performance tuning of deep learning training in Amazon SageMaker

GPUs can significantly speed up deep learning training, and have the potential to reduce training time from weeks to just hours. However, to fully benefit from the use of GPUs, you should consider the following aspects: Optimizing code to make sure that underlying hardware is fully utilized Using the latest high performant libraries and GPU […]

Giving your content a voice with the Newscaster speaking style from Amazon Polly

Audio content consumption has grown exponentially in the past few years. Statista reports that podcast ad revenue will exceed a billion dollars in 2021. For the publishing industry and content providers, providing audio as an alternative option to reading could improve engagement with users and be an incremental revenue stream. Given the shift in customer […]