AWS Machine Learning Blog

Amazon Rekognition is a service that makes it easy to add image analysis to your applications. It’s based on the same proven, highly scalable, deep learning technology developed by Amazon’s computer vision scientists to analyze billions of images daily for Amazon Prime Photos. Facial recognition enables you to find similar faces in a large collection […]

This is a guest post by Jaeyoung Choi of the International Computer Science Institute and Kevin Li of the University of California, Berkeley. This project demonstrates how academic researchers can leverage our AWS Cloud Credits for Research Program to support their scientific breakthroughs. Modern mobile devices can automatically assign geo-coordinates to images when you take pictures of […]

This guest post is by AWS Community Hero Cyrus Wong. Cyrus is a Data Scientist at the Hong Kong Vocational Education (Lee Wai Lee) Cloud Innovation Centre. He has achieved all 7 AWS Certifications and enjoys sharing his AWS knowledge with others through open-source projects, blog posts, and events. HowWhoFeelInVideo is an application that analyzes […]

Apache MXNet (incubating) is a full-featured, highly scalable deep learning framework that supports creating and training state-of-the-art deep learning models. With it, you can create convolutional neural networks (CNNs), long short-term memory networks (LSTMs), and others. It supports a variety of languages, including, but not limited to, Python, Scala, R, and Julia. In this post, we showcase […]

Imagine capturing frames off of live video streams, identifying objects within the frames, and then triggering actions or notifications based on the identified objects. Now imagine accomplishing all of this with low latency and without a single server to manage In this post, I present a serverless solution that uses Amazon Rekognition and other AWS […]

The AWS Deep Learning AMI lets you build and scale deep learning applications in the cloud, at any scale. The AMI comes pre-installed with popular deep learning frameworks, to let you to train sophisticated, custom AI models, experiment with new algorithms, or to learn new skills and techniques. The latest release of the AWS Deep […]

Have you ever wondered how you can use machine learning (ML) for translation? With our new framework, Sockeye, you can model machine translation (MT) and other sequence-to-sequence tasks. Sockeye, which is built on Apache MXNet, does most of the heavy lifting for building, training, and running state-of-the-art sequence-to-sequence models. In natural language processing (NLP), many […]

Listen to this post Voiced by Amazon Polly This is a guest post by Yiannis Philipopoulos, a Software Developer at Bandwidth. In Yiannis’ words: “Bandwidth’s solutions are shaping the future of how we connect with voice and messaging for mobile apps and large-scale, enterprise-level solutions. At the core of Bandwidth’s business-grade Communications Platform as a […]

To increase the accuracy of speech recognition for conversations over the phone, Amazon Lex now supports telephony audio (8 kHz). You can now employ the same deep learning technology as Amazon Alexa to converse with your applications and fulfill the most common requests. Amazon Lex maintains context and dynamically manages the dialogue, adjusting responses based […]

The Kelley Blue Book Bot allows users to get real-time Kelley Blue Book® Trade-In Value for vehicles using natural language. Users can interact with the chatbot in both voice and text. A simple question like, “Kelley Blue Book, can you tell me the trade-in value for my 2012 Honda Civic?” is all that is needed […]