AWS Machine Learning Blog

Category: Artificial Intelligence

Use AWS Machine Learning to Analyze Customer Calls from Contact Centers (Part 2): Automate, Deploy, and Visualize Analytics using Amazon Transcribe, Amazon Comprehend, AWS CloudFormation, and Amazon QuickSight

In the previous blog post, we showed you how to string together Amazon Transcribe and Amazon Comprehend to be able to conduct sentiment analysis on call conversations from contact centers. Here, we demonstrate how to leverage AWS CloudFormation to automate the process and deploy your solution at scale. Solution Architecture The following diagram illustrates architecture that […]

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Transcribe speech in three new languages: French, Italian, and Brazilian Portuguese

We’re excited to announce that Amazon Transcribe now supports automatic speech recognition in three new languages: French, Italian, and Brazilian Portuguese. These new languages expand upon the 5 languages already available in Amazon Transcribe: US English, US Spanish, Australian English, British English, and Canadian French. Using the Amazon Transcribe API, you can analyze audio files […]

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Amazon SageMaker adds Scikit-Learn support

Amazon SageMaker now comes pre-configured with the Scikit-Learn machine learning library in a Docker container. Scikit-Learn is popular choice for data scientists and developers because it provides efficient tools for data analysis and high quality implementations of popular machine learning algorithms through a consistent Python interface and well documented APIs. Scikit-Learn executes quickly and can […]

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Power your website with on-demand translated reviews using Amazon Translate

Amazon Translate is a high-quality neural machine translation service that uses advanced deep learning techniques to provide fast language translation of content from a source language to a target language, chosen among the supported pairs. It enables developers to easily invoke an API providing the text to be translated and obtain its translated version in real-time, hiding the complexity of building a neural machine translation model.

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Easily train models using datasets labeled by Amazon SageMaker Ground Truth

Data scientists and developers can now easily train machine learning models on datasets labeled by Amazon SageMaker Ground Truth. Amazon SageMaker Training now accepts the labeled datasets produced in augmented manifest format as input through both AWS Management Console and Amazon SageMaker Python SDK APIs. Last month during AWS re:Invent, we launched Amazon SageMaker Ground […]

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Analyzing contact center calls—Part 1: Use Amazon Transcribe and Amazon Comprehend to analyze customer sentiment

Contact centers aiming to improve overall operational efficiency have an imperative to understand caller-agent dynamics. In part one of this two-part blog post series we’ll show you how you can use Amazon Transcribe and Amazon Comprehend to transform call recordings from audio to text and then run sentiment analysis on the transcripts. We will demonstrate how […]

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Scalable multi-node training with TensorFlow

We’ve heard from customers that scaling TensorFlow training jobs to multiple nodes and GPUs successfully is hard. TensorFlow has distributed training built-in, but it can be difficult to use. Recently, we made optimizations to TensorFlow and Horovod to help AWS customers scale TensorFlow training jobs to multiple nodes and GPUs. With these improvements, any AWS customer […]

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Amazon SageMaker Automatic Model Tuning now supports early stopping of training jobs

In June 2018, we launched Amazon SageMaker Automatic Model Tuning, a feature that automatically finds well-performing hyperparameters to train a machine learning model with. Unlike model parameters learned during training, hyperparameters are set before the learning process begins. A typical example of the use of hyperparameters is the learning rate of stochastic gradient procedures. Using […]

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Anomaly detection on Amazon DynamoDB Streams using the Amazon SageMaker Random Cut Forest algorithm

Have you considered introducing anomaly detection technology to your business? Anomaly detection is a technique used to identify rare items, events, or observations which raise suspicion by differing significantly from the majority of the data you are analyzing.  The applications of anomaly detection are wide-ranging including the detection of abnormal purchases or cyber intrusions in […]

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Announcing the Winners of the 2018 AWS AI Hackathon

We’re excited to announce the winners of the 2018 AWS AI Hackathon.  Horacio Canales has won first place with his “Second Alert” project. This project enables users from around the world to identify missing persons, including human trafficking victims, children too young to remember their family members’ names, and mentally handicapped individuals. Horacio built the […]

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