AWS Machine Learning Blog

AWS AI Blog Month in Review: March 2017

by Derek Young | on | Permalink | Comments |  Share

We’ve just finished another month of AI solutions on the AWS AI Blog. Please take a look at our summaries below and learn, comment, and share. Thanks for reading! NEW POSTS Deploy Deep Learning Models on Amazon ECS In this post, learn how to connect the workflow between the data scientists and DevOps. Using a […]

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Deploy Deep Learning Models on Amazon ECS

by Asif Khan | on | Permalink | Comments |  Share

Artificial intelligence (AI) is the computer science field dedicated to solving cognitive problems commonly associated with human intelligence, such as learning, problem solving, and pattern recognition. Machine learning (ML) and deep learning (DL) are computer science fields derived from the AI discipline. Most ML and DL systems have two distinct parts: training (or learning) and […]

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Amazon at WMT: Improving Machine Translation with User Feedback

by Kellen Sunderland | on | Permalink | Comments |  Share

Machine translation is one of the most exciting and important applications of machine learning.  It’s a widely researched topic, both in the academic community and within major technology companies, such as Amazon.  At Amazon, we use machine translation to do things like document the same products in multiple languages.  This helps us to offer additional […]

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Build Your Own Text-to-Speech Applications with Amazon Polly

In general, speech synthesis isn’t easy.  You can’t just assume that when an application reads each letter of a sentence the output will make sense. A few common challenges for text-to-speech applications include: Words that are written the same way, but that are pronounced differently: I live in Las Vegas. vs. This presentation broadcasts live […]

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AI Tech Talk: How to Get the Most Out of Amazon Polly, a Text-to-Speech Service

Although there are many ways to optimize the speech generated by Amazon Polly‘s text-to-speech voices, new customers may find it challenging to quickly learn how to apply the most effective enhancements in each situation. The objective of this webinar is to educate customers about all of the ways in which they can modify the speech […]

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Updated AWS CloudFormation Deep Learning Template Adds New Features and Capabilities

by Naveen Swamy | on | Permalink | Comments |  Share

Listen to this post Voiced by Amazon Polly AWS CloudFormation, which creates and configures Amazon Web Services resources with a template, simplifies the process of setting up a distributed deep learning cluster. The AWS CloudFormation Deep Learning template uses the latest updated Amazon Deep Learning AMI (which provides Apache MXNet, TensorFlow, Caffe, Theano, Torch, and CNTK […]

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Use Amazon Rekognition to Build an End-to-End Serverless Photo Recognition System

Imagine you work for a marketing agency that has tens of thousands of stock images. You find that many images don’t have descriptive file names and others are completely mislabeled. You don’t want to spend hours and hours relabeling them and moving them around to different folders. But what if you could find the images […]

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AWS Collaborates With the National Science Foundation to Foster Innovation

by Sanjay Padhi | on | Permalink | Comments |  Share

Listen to this post Voiced by Amazon Polly Amazon Web Services and the National Science Foundation (NSF) are collaborating to foster innovation in big data research. Under the AWS Research Initiative (ARI) program, AWS and NSF will respectively support innovative research in the field of Big Data. With the advancements of techniques and technologies such […]

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Month in Review: February 2017

by Derek Young | on | Permalink | Comments |  Share

The AWS AI Blog launched in February! Take a look at our summaries below and learn, comment, and share. Thanks for reading! NEW POSTS Welcome to the New AWS AI Blog! If you ask 100 people for the definition of “artificial intelligence,” you’ll get at least 100 answers, if not more. At AWS, we define […]

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Predicting Customer Churn with Amazon Machine Learning

by Denis V. Batalov | on | Permalink | Comments |  Share

Note: This post has a companion talk that was delivered at AWS re:Invent 2016. Losing customers is costly for any business. Identifying unhappy customers early on gives you a chance to offer them incentives to stay. This post describes using machine learning (ML) for the automated identification of unhappy customers, also known as customer churn […]

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