AWS Machine Learning Blog

Amazon Polly Adds 9 AWS Regions, Korean Language Support, and a New Indian English Voice

Amazon Polly is an AWS service that turns text into lifelike speech. Today, we are excited to announce that Amazon Polly is available in nine additional Regions, expanding the total number of Regions where Polly is available to 14. We are also excited to announce the release of  Korean language support, and that we have […]

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New AWS Deep Learning AMIs for Machine Learning Practitioners

We’re excited to announce the availability of two new versions of the AWS Deep Learning AMI. The first is a Conda-based AMI with separate Python environments for deep learning frameworks created using Conda—a popular open source package and environment management tool. The second is a Base AMI with GPU drivers and libraries to deploy your own […]

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Getting Started with the AWS Deep Learning Conda and Base AMIs

Today AWS announced the availability of two new versions of the AWS Deep Learning AMI: a Conda-based AMI and a Base AMI. This post will walk you through the instructions and additional resources for making the most of your new AMIs. New Deep Learning AMI with Conda-managed environments The new Deep Learning AMIs for Amazon […]

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Building an Autonomous Vehicle Part 3: Connecting Your Autonomous Vehicle

by Justin De Castri | on | Permalink | Comments |  Share

In the first blog post in our autonomous vehicle series, you built your Donkey vehicle and deployed your pilot server onto an Amazon EC2 instance. In the second blog, you learned to drive the Donkey car, and the Donkey car learned to drive itself. In this blog post, we’ll cover the process of streaming telemetry […]

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Matrix Analytics Uses Deep Learning on AWS to Boost Early Cancer Detection

by Cynthya Peranandam | on | Permalink | Comments |  Share

Matrix Analytics is helping to save lives. The Colorado-based startup uses deep learning on Amazon Web Services (AWS) to track disease progression for patients diagnosed with pulmonary nodules in their lungs. While often benign, careful monitoring and follow-up care are critical to knowing if and when those nodules will turn into malignant tumors. The company’s […]

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Modify the Timbre of Amazon Polly Voices with the New Vocal Tract SSML Feature

Today, the Amazon Polly team is pleased to announce the release of a new Speech Synthesis Markup Language (SSML) feature that allows developers to modify the timbre of any Text-to-Speech (TTS) voice. This is a compelling feature for customers who want to customize an existing voice in the Amazon Polly portfolio to make it sound […]

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Apache MXNet Version 0.12 Extends Gluon Functionality to Support Cutting Edge Research

Last week, the Apache MXNet community released version 0.12 of MXNet. The major features were support for NVIDIA Volta GPUs and sparse tensors. The release also included a number of new features for the Gluon programming interface. In particular, these features make it easier to implement cutting-edge research in your deep learning models: Variational dropout, […]

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Understand Movie Star Social Networks Using Amazon Rekognition and Graph Databases

Amazon Rekognition is an AWS service that makes it easy to add image analysis to your applications. The latest feature added to the API for this deep-learning-powered computer vision is Celebrity Recognition. This simple-to-use functionality detects and recognizes thousands of individuals who are famous, noteworthy, or prominent in their field. Users can harness the tool […]

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AWS Collaborates with Emory University to Develop Cloud-Based NLP Research Platform Using Apache MXNet

by Jinho Choi and Joseph Spisak | on | Permalink | Comments |  Share

Natural Language Processing (NLP) is a research field in artificial intelligence that aims to develop computer programs’ understanding of human (natural) language. Even if you don’t know much about NLP, there is a good chance that you have been using it daily. Whenever you type a word using the virtual keyboard on your phone, it […]

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Monitoring GPU Utilization with Amazon CloudWatch

Deep learning requires a large amount of matrix multiplications and vector operations that can be parallelized by GPUs (graphics processing units) because GPUs have thousands of cores. Amazon Web Services allows you to spin up P2 or P3 instances that are great for running Deep Learning frameworks such as MXNet, which emphasizes speeding up the deployment […]

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