AWS Machine Learning Blog

Course Hero is an online learning platform that provides students access to over 25 million course-specific study materials, including study guides, class notes, and practice problems for numerous subjects. The platform, which runs on AWS, is designed to enable every student to take on their courses feeling confident and prepared. To make that possible, Course […]

Voice-powered experiences are gaining traction and customer love. Volley is at the cutting edge of voice-controlled entertainment with its series of popular smart-speaker games, and many aspects of Volley rely on Amazon Polly. Every day, more and more people switch on lights, check the weather, and play music not by pushing buttons but with verbal […]

Note: Amazon Elastic Inference is no longer available. Please see Amazon SageMaker for similar capabilities. Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances, and reduce the cost of running deep learning inference by up to 75 percent. The EIPredictorAPI makes it easy to use Elastic Inference. In this post, […]

Deep learning (DL) frameworks enable machine learning (ML) practitioners to build and train ML models. However, the process of deploying ML models in production to serve predictions (also known as inferences) in real time is more complex. It requires that ML practitioners build a scalable and performant model server, which can host these models and […]

Listening to your Microsoft Word documents as audio is a great way to save time or to be productive on a long commute. You can easily convert an entire block of text into MP3 format with Amazon Polly. But you can vastly improve your listening experience with just a few simple steps. In this blog […]

Amazon Transcribe is a fully-managed automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capabilities to applications. Depending on your use case, you may have domain-specific terminology that doesn’t transcribe properly (e.g. “EBITDA” or “myocardial infarction”). In this post, we will show you how to leverage the custom vocabulary feature […]

Remember the screech of the dial-up and plain-text websites? It was in that era that the Amazon.com website launched in the summer of 1995. Like the rest of the web, Amazon.com has gone through a digital experience makeover that includes slick web controls, rich media, multi-channel support, and intelligent content placement. Nonetheless, there are certain […]

Training and inference are crucial components of a machine learning (ML) development cycle. During the training phase, you teach a model to address a specific problem. Through this process, you obtain binary model files ready for use in production. For inference, you can choose among several framework-specific solutions for model deployment, such as TensorFlow Serving […]

When you run predictions on large datasets, you may want to drop some input attributes before running the predictions. This is because those attributes don’t carry any signal or were not part of the dataset used to train your machine learning (ML) model. Similarly, it can be helpful to map the prediction results to all […]

Apache MXNet is an open-source deep learning software framework used to train and deploy deep neural networks. Data scientists and machine learning (ML) developers love MXNet due to its flexibility and efficiency when building deep learning models. Amazon SageMaker is committed to improving the customer experience for all ML frameworks and libraries, including MXNet. With the latest release of […]