AWS Machine Learning Blog

Introducing the Amazon ML Solutions Lab

We are excited to announce the Amazon ML Solutions Lab, a new program that connects machine learning experts from across Amazon with AWS customers to help identify novel uses of machine learning inside customers’ businesses, and guide them in developing new machine learning-enabled features, products, and processes. Amazon has been investing in machine learning for more than 20 years, innovating in areas such as fulfilment and logistics, personalization and recommendations, forecasting, fraud prevention, and supply chain optimization. The Amazon ML Solutions Lab provides you access to the same talent that built many of Amazon’s machine learning-powered products and services.

Amazon Rekognition Announces Real-Time Face Recognition, Support for Recognition of Text in Image, and Improved Face Detection

Amazon Rekognition today announces three new features: detection and recognition of text in images, real-time face recognition across tens of millions of faces, and detection of up to 100 faces in challenging crowded photos. Customers who are already using Amazon Rekognition for face verification and identification will experience up to a 10% accuracy improvement in most cases.

Run Deep Learning Frameworks with GPU Instance Types on Amazon EMR

Today, AWS is excited to announce support for Apache MXNet and new generation GPU instance types on Amazon EMR, which enables you to run distributed deep neural networks alongside your machine learning workflows and big data processing. Additionally, you can install and run custom deep learning libraries on your EMR clusters with GPU hardware. Through […]

Building an Autonomous Vehicle, Part 4:  Using Behavioral Cloning with Apache MXNet for Your Self-Driving Car

In the first blog post of our autonomous vehicle series, you built your Donkey vehicle and deployed your pilot server onto an Amazon EC2 instance. In the second blog post, you learned to drive the Donkey car, and the Donkey car learned to self-drive. In the third blog post, you learned about the process of streaming telemetry […]

Announcing ONNX Support for Apache MXNet

Today, AWS announces the availability of ONNX-MXNet, an open source Python package to import Open Neural Network Exchange (ONNX) deep learning models into Apache MXNet. MXNet is a fully featured and scalable deep learning framework that offers APIs across popular languages such as Python, Scala, and R. With ONNX format support for MXNet, developers can […]

Amazon Polly Adds 9 AWS Regions, Korean Language Support, and a New Indian English Voice

Amazon Polly is an AWS service that turns text into lifelike speech. Today, we are excited to announce that Amazon Polly is available in nine additional Regions, expanding the total number of Regions where Polly is available to 14. We are also excited to announce the release of  Korean language support, and that we have […]

New AWS Deep Learning AMIs for Machine Learning Practitioners

We’re excited to announce the availability of two new versions of the AWS Deep Learning AMI. The first is a Conda-based AMI with separate Python environments for deep learning frameworks created using Conda—a popular open source package and environment management tool. The second is a Base AMI with GPU drivers and libraries to deploy your own […]

Matrix Analytics Uses Deep Learning on AWS to Boost Early Cancer Detection

Matrix Analytics is helping to save lives. The Colorado-based startup uses deep learning on Amazon Web Services (AWS) to track disease progression for patients diagnosed with pulmonary nodules in their lungs. While often benign, careful monitoring and follow-up care are critical to knowing if and when those nodules will turn into malignant tumors. The company’s […]