AWS Machine Learning Blog
Category: Artificial Intelligence
Using Amazon Polly to Provide Real-Time Home Monitoring Alerts
This is a guest blog post by Siva K. Syamala, Senior Developer from Y-cam Solutions. In their own words, “Y-cam is a provider of high quality security video solutions, our vision is to make smart home security easy and accessible to all.” Home security is a very important constituent in home automation and the use […]
Read MoreBuild an Autonomous Vehicle on AWS and Race It at the re:Invent Robocar Rally
Autonomous vehicles are poised to take to our roads in massive numbers in the coming years. This has been made possible due to advances in deep learning and its application to autonomous driving. In this post, we take you through a tutorial that shows you how to build a remote control (RC) vehicle that uses […]
Read MoreBuild 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 […]
Read MoreTwo 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. […]
Read MoreCreate a Question and Answer Bot with Amazon Lex and Amazon Alexa
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 for your customers? Interestingly, a recent poll shows that 44% of people would rather talk to a chat bot than to a human! In this post we provide a sample solution, called QnABot (pronounced “Q and A Bot”). The QnABot uses Amazon Lex and Amazon Alexa to provide a conversational interface for your “Questions and Answers.” This allows your users to ask their questions and get quick and relevant answers.
Read MoreAWS 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 […]
Read MoreGet 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. For users of all levels, AWS recommends Amazon SageMaker, a fully managed machine learning (ML) platform. The platform makes it straightforward to quickly and easily build, train, and deploy ML […]
Read MoreEnhancements 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 […]
Read MoreExport 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 […]
Read MoreBring 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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