AWS Machine Learning Blog

Easily perform bulk label quality assurance using Amazon SageMaker Ground Truth

In this blog post we’re going to walk you through an example situation where you’ve just built a machine learning system that labels your data at volume and you want to perform manual quality assurance (QA) on some of the labels. How can you do so without overwhelming your limited resources?  We’ll show you how, […]

Improving Patient Care with Machine Learning At Beth Israel Deaconess Medical Center

Beth Israel Deaconess Medical Center has launched a multi-year, innovative research program on how machine learning can improve patient care, supported by an academic research sponsorship grant from AWS.  The Harvard Medical School-affiliated teaching hospital will use a broad array of AWS machine learning services to uncover new ways that machine learning technology can enhance […]

Use two additional data labeling services for your Amazon SageMaker Ground Truth labeling jobs

We’re excited to announce the availability of two more data labeling services that you can use for your Amazon SageMaker Ground Truth labeling jobs: Data Labeling Services by iMerit’s US-based workforce Data Labeling Services by Startek, Inc. These new listings on the AWS Marketplace supplement the existing iMerit India-based workforce listing to provide you a […]

Preprocess input data before making predictions using Amazon SageMaker inference pipelines and Scikit-learn

Amazon SageMaker enables developers and data scientists to build, train, tune, and deploy machine learning (ML) models at scale. You can deploy trained ML models for real-time or batch predictions on unseen data, a process known as inference. However, in most cases, the raw input data must be preprocessed and can’t be used directly for […]

Identifying bird species on the edge using the Amazon SageMaker built-in Object Detection algorithm and AWS DeepLens

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. Custom object detection has become an important enabler for […]

Newstag improves global video news discoverability using AI language services on AWS

Swedish startup Newstag uses artificial intelligence (AI) to allow customers to create personalized video news channels from major global news providers. Their mission is to continuously empower people and organizations with the latest, diverse information. To increase discoverability of video news from all around the world for their customers, Newstag creates rich metadata for each […]

Run ONNX models with Amazon Elastic Inference

At re:Invent 2018, AWS announced Amazon Elastic Inference (EI), a new service that lets you attach just the right amount of GPU-powered inference acceleration to any Amazon EC2 instance. This is also available for Amazon SageMaker notebook instances and endpoints, bringing acceleration to built-in algorithms and to deep learning environments. In this blog post, I […]

Machine learning: What’s in it for government?

Machine learning (ML) allows governments to deliver better, more cost-effective, and citizen-friendly services. We talked with three Amazon Web Services (AWS) customers from government authorities and institutes who shared their stories about how ML helped them transform their services and their organizations. These customers gathered at an executive learning track curated particularly for European Government […]

Creating hierarchical label taxonomies using Amazon SageMaker Ground Truth

At re:Invent 2018 we launched Amazon SageMaker Ground Truth, which can Build Highly Accurate Datasets and Reduce Labeling Costs by up to 70% using machine learning. Amazon SageMaker Ground Truth offers easy access to public and private human labelers and provides them with built-in workflows and interfaces for common labeling tasks. Additionally, Amazon SageMaker Ground […]

Using TensorFlow eager execution with Amazon SageMaker script mode

In this blog post, I’ll discuss how to use Amazon SageMaker script mode to train models with TensorFlow’s eager execution mode. Eager execution is the future of TensorFlow; although it is available now as an option in recent versions of TensorFlow 1.x, it will become the default mode of TensorFlow 2. I’ll provide a brief […]