AWS Machine Learning Blog

Category: Amazon Comprehend

Get started with automated metadata extraction using the AWS Media Analysis Solution

You can easily get started extracting meaningful metadata from your media files by using the Media Analysis Solution on AWS. The Media Analysis Solution provides AWS CloudFormation templates that you can use to start extracting meaningful metadata from your media files within minutes. With a web-based user interface, you can easily upload files and see the metadata that is automatically extracted. This solution uses Amazon Rekognition for facial recognition, Amazon Transcribe to create a transcript, and Amazon Comprehend to run sentiment analysis on the transcript. You can also upload your own images to an Amazon Rekognition collection and train the solution to recognize individuals. In this blog post, we’ll show you step-by step how to launch the solution and upload an image and video. You’ll be able to see firsthand how metadata is seamlessly extracted.

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TINT uses Amazon Comprehend to find and aggregate the best social media content for customers

TINT is a simple, DIY platform that helps brands find, curate, and display their most effective customer-generated content from social media on marketing channels such as websites, mobile apps, and event displays. Businesses can link their Twitter, YouTube, Pinterest, Instagram, Facebook, and RSS feeds to their TINT accounts The social media aggregator uses machine learning […]

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Announcing the Artificial Intelligence (AI) Hackathon: Build Intelligent Applications using machine learning APIs and serverless

Amazon Web Services (AWS) brings image and video analysis, natural language processing, speech recognition, text-to-speech, and machine translation within the reach of every developer. With machine learning (ML) services by AWS, you can plug in prebuilt AI functionality into your apps without having to worry about ML models. Thousands of developers have used Amazon ML […]

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Amazon Comprehend now supports Syntax Analysis

We’re excited to announce that Amazon Comprehend now provides a Syntax API.  This enables you to tokenize text (for example, to extract word boundaries) and the corresponding part of speech (PoS) for each word. Today, Amazon Comprehend enables analysis use cases like such as knowing whether a customer comment is negative or positive, and identifying […]

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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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VidMob combines computer vision and language AI services for data-driven creative asset production

VidMob is a social video creation platform that marketers of all sizes can use to develop personalized advertising communications at scale. VidMob uses machine learning (ML) to power its SaaS application. This application uses metadata extraction and sentiment analysis to provide marketers with actionable insights into which creative assets resonate with their intended audience, and […]

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How to scale sentiment analysis using Amazon Comprehend, AWS Glue and Amazon Athena

Today consumers are encouraged to express their satisfaction or frustration with a company or product through social media, blogs, and review platforms. Sentiment analysis can help companies better understand their customers’ opinions and needs and make more informed business decisions. Amazon released a dataset to the public with over 130 million product reviews in multiple […]

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Build text analytics solutions with Amazon Comprehend and Amazon Relational Database Service

In this blog post, we will show you how to get started building rich text analytics views from your database, without having to learn anything about machine learning for natural language processing models. We’ll do this by leveraging Amazon Comprehend, paired with Amazon Aurora-MySQL and AWS Lambda.

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Build smart chat apps with Amazon machine learning APIs and the PubNub ChatEngine

The demand for chat apps is growing wildly. From social apps to business collaboration, in-game chat to customer support, every app needs chat. Chat apps like Telegram are making mainstream news and generating widespread interest.

Historically, building a scalable, feature-rich chat app was surprisingly difficult. Not anymore. PubNub ChatEngine has integrated Amazon machine learning APIs, which makes building intelligent, scalable chat apps super easy for mobile and web.

In this blog post, you’ll learn how to spin up the PubNub ChatEngine and add Amazon Translate and Amazon Polly for cross-lingual, speech-enabled chat apps that you can embed anywhere.

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ClearView Social uses Amazon Comprehend to measure the impact of social sharing

ClearView Social enables a company’s employees to share approved content on LinkedIn, Twitter, and other social networks with a single click. It then broadcasts the content to those social networks at peak times, and tracks the resulting engagement with a leaderboard and an analytics dashboard. According to Bill Boulden, CTO of ClearView Social, a key […]

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