AWS Machine Learning Blog

Build a Voice Kit with Amazon Lex and a Raspberry Pi

In this post, we show how you can embed Amazon Lex into custom hardware using widely available components. We demonstrate how you can build a simple voice-based AI kit and connect it to Amazon Lex. We’ll use a Raspberry Pi and a few off-the-shelf components totaling less than $60. By the end of this blog […]

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Two New Courses are Now Available for Machine Learning and Deep Learning on AWS

AWS Training and Certification helps you advance your knowledge with practical skills so you can get more out of the AWS Cloud. We now have two new courses to help you learn about how to leverage artificial intelligence (AI) solutions using AWS: Introduction to Machine Learning web-based training and Deep Learning on AWS instructor-led training. […]

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Create a Question and Answer Bot with Amazon Lex and Amazon Alexa

by Bob Strahan and John Calhoun | on | in Amazon Lex* | Permalink | Comments |  Share

Your users have questions and you have answers, but you need a better way for your users to ask their questions and get the right answers. They often call your help desk, or post to your support forum, but over time this adds stress and cost to your organization. Could a chat bot add value […]

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AWS Deep Learning AMI Now Includes Apache MXNet 0.11 and TensorFlow 1.3

The AWS Deep Learning Amazon Machine Image (AMI) is designed to help you build stable, secure, and scalable deep learning applications on AWS. The AMI comes pre-installed with popular deep learning frameworks. It has GPU drivers and libraries that let you train sophisticated AI models and scale them in the cloud. The latest release of […]

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Get Started with Deep Learning Using the AWS Deep Learning AMI

Whether you’re new to deep learning or want to build advanced deep learning projects in the cloud, it’s easy to get started by using AWS. The AWS Deep Learning AMIs, available in both Ubuntu and Amazon Linux versions, let you run deep learning applications in the cloud at any scale. The Amazon Machine Images (AMIs) […]

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Enhancements to the Amazon Lex Console Let You Test Your Bot for Better Troubleshooting

Building your chatbot in the Amazon Lex console takes just a few steps, and testing your bot is just as easy. We’ve made enhancements to the Test window of the Amazon Lex console which now provides you more details during testing and enables easier bot troubleshooting. Once you’ve built a bot to test, the Test […]

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NIPS 2017 Challenge Pushes Deep Learning to Improve Surgical Outcomes

by Lukasz Kidzinski and Sunil Mallya | on | Permalink | Comments |  Share

AWS, NVIDIA, Stanford, EPFL, and UC Berkeley have joined forces to tackle clinical problems in biomechanics. The NIPS 2017 Learning to Run challenge brings together over 300 researchers, engineers, and enthusiasts from around the world to apply deep learning to medical research. The challenge will culminate at the international AI conference Neural Information Processing Systems […]

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Combining Deep Learning Networks (GAN and Siamese) to Generate High-Quality, Life-Like Images

by Guy Ernest | on | Permalink | Comments |  Share

Because deep learning relies on the amount and quality of the data that is used to train it, companies spend a lot to get good image data. Typically, they use either expensive human annotation or other labor-intensive tasks, such as taking more photos of products or people. This approach is costly, and it doesn’t scale. […]

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Export your Amazon Lex bot schema to the Alexa Skills Kit

You can now export your Amazon Lex chatbot schema into the Alexa Skills Kit to simplify the process of creating an Alexa skill. Amazon Lex now provides the ability to export your Amazon Lex chatbot definition as a JSON file that can be added to the Alexa Skills Kit (ASK). Once you add the bot schema file […]

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Bring Machine Learning to iOS apps using Apache MXNet and Apple Core ML

With the release of Core ML by Apple at WWDC 2017, iOS, macOS, watchOS and tvOS developers can now easily integrate a machine learning model into their app. This enables developers to bring intelligent new features to users with just a few lines of code. Core ML makes machine learning more accessible to mobile developers. […]

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