AWS Machine Learning Blog

Exploiting the Unique Features of the Apache MXNet Deep Learning Framework with a Cheat Sheet

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 […]

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Create a Serverless Solution for Video Frame Analysis and Alerting

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 […]

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The AWS Deep Learning AMI for Ubuntu is Now Available with CUDA 8, Ubuntu 16, and the Latest Versions of Deep Learning Frameworks

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 […]

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Train Neural Machine Translation Models with Sockeye

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 […]

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Building a Reliable Text-to-Speech Service with Amazon Polly

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 […]

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Amazon Lex Now Supports Telephony Audio (8 kHz) for Increased Speech Recognition Accuracy

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 […]

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Voice-Enabled Mobile Bot Drives Auto Industry Innovation with Real-Time Trade-in Values for Vehicles

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 […]

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Using Amazon Polly to Deliver Health Care for People with Long-Term Conditions

This is a guest post by Michael Wray, senior software architect at Inhealthcare. Founded in 2012, Inhealthcare has created a digital infrastructure which supports remote home monitoring for the entire UK population. Listen to this post Voiced by Amazon Polly   With an aging population that continues to grow, healthcare is being changed forever. Are […]

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Build PMML-based Applications and Generate Predictions in AWS

If you generate machine learning (ML) models, you know that the key challenge is exporting and importing them into other frameworks to separate model generation and prediction. Many applications use PMML (Predictive Model Markup Language) to move ML models from one framework to another. PMML is an XML representation of a data mining model. In […]

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