AWS Machine Learning Blog

Category: Top Posts

AWS IQ waives fees until June 30, 2020, to help you stand up and scale remote work initiatives

The recent post Working from Home? Here’s How AWS Can Help shared several ways AWS is helping you set up and scale remote work and work-from-home initiatives. Getting these solutions set up is sometimes best—and achieved more quickly—with expert help. You can get the help you need with AWS IQ, which connects you to AWS […]

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Creating a machine learning-powered REST API with Amazon API Gateway mapping templates and Amazon SageMaker

Amazon SageMaker enables organizations to build, train, and deploy machine learning models. Consumer-facing organizations can use it to enrich their customers’ experiences, for example, by making personalized product recommendations, or by automatically tailoring application behavior based on customers’ observed preferences. When building such applications, one key architectural consideration is how to make the runtime inference […]

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Build a unique Brand Voice with Amazon Polly

AWS is pleased to announce a new feature in Amazon Polly called Brand Voice, a capability in which you can work with the Amazon Polly team of AI research scientists and linguists to build an exclusive, high-quality, Neural Text-to-Speech (NTTS) voice that represents your brand’s persona. Brand Voice allows you to differentiate your brand by […]

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AWS announces the Machine Learning Embark program to help customers train their workforce in machine learning

Today at AWS re:Invent 2019, I’m excited to announce the AWS Machine Learning (ML) Embark program to help companies transform their development teams into machine learning practitioners. AWS ML Embark is based on Amazon’s own experience scaling the use of machine learning inside its own operations as well as the lessons learned through thousands of […]

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Automatically extract text and structured data from documents with Amazon Textract

Documents are a primary tool for record keeping, communication, collaboration, and transactions across many industries, including financial, medical, legal, and real estate. The millions of mortgage applications and hundreds of millions of W2 tax forms processed each year are just a few examples of such documents. A lot of information is locked in unstructured documents. […]

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Amazon SageMaker automatic model tuning now supports random search and hyperparameter scaling

We are excited to introduce two highly requested features to automatic model tuning in Amazon SageMaker: random search and hyperparameter scaling. This post describes these features, explains when and how to enable them, and shows how they can improve your search for hyperparameters that perform well. If you are in a hurry, you’ll be happy […]

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Simplify machine learning with XGBoost and Amazon SageMaker

Machine learning is a powerful tool that has recently enabled use cases that were never previously possible–computer vision, self-driving cars, natural language processing, and more. Machine learning is a promising technology, but it can be complex to implement in practice. In this blog post, we explain XGBoost—a machine learning library that is simple, powerful, and […]

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