AWS Machine Learning Blog

Category: Artificial Intelligence

Building a scalable and adaptable video processing pipeline with Amazon Rekognition Video

This is a guest post by Joe Monti, Sr. Software Engineer at VidMob. Vidmob is, in their own words, “the world’s leading video creation platform, with innovative technology solutions that enable a network of highly trained creators to develop marketing communications that are insight-driven, personalized, and scalable. VidMob creators are trained to produce the full […]

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Are you ready for a new challenge? You have an opportunity to make a difference! Announcing the AWS DeepLens Challenge

Technology like machine learning (ML) has the potential to profoundly impact the world, and we believe, benefit society in materially beneficial ways. It’s one of the reasons why AWS is committed to putting machine learning into the hands of every developer and data scientist. And now, with the AWS DeepLens deep learning-enabled video camera, developers […]

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Monitor Amazon Transcribe applications with AWS CloudTrail and Amazon CloudWatch Events

Monitoring your AWS resources is critical for security, performance, compliance, and cost control purposes. Therefore, our customers always ask for features to enable monitoring. Today, we are pleased to announce that Amazon Transcribe is integrated with AWS CloudTrail and Amazon CloudWatch Events to give you more visibility and control of your Amazon Transcribe resources. Let’s […]

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Amazon Comprehend now supports asynchronous processing along with larger document sizes

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text.  Starting today, you have the option to analyze a collection of documents stored in an Amazon S3 bucket using our new asynchronous job service. This is in addition to single and multiple document synchronous calls […]

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Build a serverless frontend for an Amazon SageMaker endpoint

Amazon SageMaker provides a powerful platform for building, training, and deploying machine learning models into a production environment on AWS. By combining this powerful platform with the serverless capabilities of Amazon Simple Storage Service (S3), Amazon API Gateway, and AWS Lambda, it’s possible to transform an Amazon SageMaker endpoint into a web application that accepts […]

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Introduction to the Amazon SageMaker Neural Topic Model

Structured and unstructured data are being generated at an unprecedented rate, so you need the right tools to help organize, search, and understand this vast amount of information, it’s challenging to make the data useful. This is especially true for unstructured data, and it’s estimated that over 80% of the data in enterprises is unstructured. Text analytics […]

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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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AWS Deep Learning AMIs Now Available in AWS GovCloud (US) Region

The AWS Deep Learning AMIs (Amazon machine images) are now available in AWS GovCloud (US), Amazon’s isolated cloud region built for sensitive data and regulated workloads. Available in Ubuntu and Amazon Linux, the AMIs provide fully-configured development environments to quickly build AI applications using popular deep learning frameworks including TensorFlow, Apache MXNet and Gluon, PyTorch, Chainer, […]

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Toyota Research Institute accelerates safe automated driving with deep learning at a global scale on AWS

Vehicles with self-driving technology can bring many benefits to society. One of the top priorities at Toyota Research Institute (TRI) is to apply the latest advancements in artificial intelligence (AI) to help Toyota produce cars that are safer, more accessible, and more environmentally friendly. To help TRI achieve their goals, they turned to deep learning […]

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Amazon SageMaker now supports PyTorch and TensorFlow 1.8

Starting today, you can easily train and deploy your PyTorch deep learning models in Amazon SageMaker. This is the fourth deep learning framework that Amazon SageMaker has added support for, in addition to TensorFlow, Apache MXNet, and Chainer.  Just like with those frameworks, now you can write your PyTorch script like you normally would and […]

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