AWS Machine Learning Blog

Category: Artificial Intelligence

Creating magical listening experiences with BlueToad and Amazon Polly

This is a guest blog post by Paul DeHart, co-owner and CEO, BlueToad. BlueToad, one of the leading global providers of digital content solutions, prioritizes innovation. Since 2017, we have enabled publishers (our customers) to provide audio versions of articles found in their digital magazines using Amazon Polly. We see that novel content experiences engage today’s […]

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Breaking news: Amazon Polly’s Newscaster voice and more authentic speech, launching today

For a long time, it was only in science fiction that machines verbalized emotions. As of today, Amazon Polly is one step closer to changing that. As we work on Amazon Polly, we’re constantly seeking to improve the voices. We hope you’ll agree that today’s announcement of not only Neural Text-to-Speech (NTTS) but also the […]

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Running Amazon Elastic Inference Workloads on Amazon ECS

Amazon Elastic Inference (EI) is a new service launched at re:Invent 2018. Elastic Inference reduces the cost of running deep learning inference by up to 75% compared to using standalone GPU instances. Elastic Inference lets you attach accelerators to any Amazon SageMaker or Amazon EC2 instance type and run inference on TensorFlow, Apache MXNet, and […]

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Building, training, and deploying fastai models with Amazon SageMaker

Deep learning is changing the world. However, much of the foundation work, such as building containers, can slow you down. This post describes how you can build, train, and deploy fastai models into Amazon SageMaker training and hosting by using the Amazon SageMaker Python SDK and a PyTorch base image. This helps you avoid the […]

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Machine learning for all developers with edX and Amazon SageMaker

Customers often ask us how to get started when they do not have a deep data science and machine learning (ML) background. At AWS, our goal is to put ML in the hands of every developer and data scientist. AWS Training and Certification has partnered with edX to help you get started quickly and easily with ML with […]

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Enabling healthcare access from home: Electronic Caregiver’s AWS-powered virtual caregiver  

When Electronic Caregiver’s founder and CEO, Anthony Dohrmann, started the company a decade ago, he was reacting to a difficult situation faced by 100 million Americans and countless individuals globally: the challenge of managing health treatment for chronic diseases. “Patients are often confused about their care instructions and non-adherence with care plans and medications schedules […]

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Creating custom labeling jobs with AWS Lambda and Amazon SageMaker Ground Truth  

Amazon SageMaker Ground Truth helps you build highly accurate training datasets for machine learning. It offers easy access to public and private human labelers, and provides them with built-in workflows and interfaces for common labeling tasks. Ground Truth can lower your labeling costs by up to 70% using automatic labeling. It works by training Ground […]

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Digging deep and solving problems: Well Data Labs applies machine learning to oil and gas challenges

When CEO Josh Churlik co-founded Well Data Labs in 2014, he was acutely aware of a bizarre dichotomy in his industry: For oil and gas companies, “downhole” innovation (that is, what happens underground) far exceeds the pace of data and analysis innovation. The data systems used then were relics of the 1990s – more homages […]

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Full ML Engineer scholarships from Udacity and the AWS DeepRacer Scholarship Challenge

The growth of artificial intelligence could create 58 million net new jobs in the next few years, states the World Economic Forum [1]. Yet, according to the Tencent Research Institute, it’s estimated that currently there are 300,000 AI engineers worldwide, but millions are needed [2]. As you can tell, there is a unique and immediate […]

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Pricing housing just right: Entrata enables apartments to fill capacity with Amazon SageMaker and 1Strategy

The housing market is complex.  There is a continuously changing supply of student housing units around any given education campus. Moreover, the accepted value of a unit continuously changes based on physical and social variables. These variables could include proximity to campus with regard to other available options, friend groups living nearby, and the availability […]

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