AWS Machine Learning Blog

Category: Artificial Intelligence

PDF document pre-processing with Amazon Textract: Visuals detection and removal

Amazon Textract is a fully managed machine learning (ML) service that automatically extracts printed text, handwriting, and other data from scanned documents that goes beyond simple optical character recognition (OCR) to identify, understand, and extract data from forms and tables. Amazon Textract can detect text in a variety of documents, including financial reports, medical records, […]

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Batch image processing with Amazon Rekognition Custom Labels 

Amazon Rekognition is a computer vision service that makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning (ML) expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as […]

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The following diagram illustrates the serverless pipeline architecture.

Translate video captions and subtitles using Amazon Translate

September 2021: This post and the solution has been updated to use the Amazon EventBridge events notifications in Amazon Translate for tracking Amazon Translate Batch Translation job completion. Video is a highly effective a highly effective way to educate, entertain, and engage users. Your company might carry a large collection of videos that include captions […]

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The following diagram illustrates this architecture covering the last three components.

Active learning workflow for Amazon Comprehend custom classification models – Part 2

This is the second in a two part series on Amazon Comprehend custom classification models. In Part 1 of this series, we looked at how to build an AWS Step Functions workflow to automatically build, test, and deploy Amazon Comprehend custom classification models and endpoints. In Part 2, we look at real-time classification APIs, feedback […]

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Active learning workflow for Amazon Comprehend custom classification models – Part 1

This is the first in a two part series on Amazon Comprehend custom classification models. In Part 1 of this series, we look at how to build an AWS Step Functions workflow to automatically build, test, and deploy Amazon Comprehend custom classification models and endpoints. In Part 2, we will look at real-time classification APIs, […]

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Introducing a new API to stop in-progress workflows in Amazon Forecast

Amazon Forecast uses machine learning (ML) to generate more accurate demand forecasts, without requiring any prior ML experience. Forecast brings the same technology used at Amazon.com to developers as a fully managed service, removing the need to manage resources or rebuild your systems. To start generating forecasts through Forecast, you can follow three steps of […]

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The following diagram illustrates the architecture of the data processing and pipeline.

Multimodal deep learning approach for event detection in sports using Amazon SageMaker

Have you ever thought about how artificial intelligence could be used to detect events during live sports broadcasts? With machine learning (ML) techniques, we introduce a scalable multimodal solution for event detection on sports video data. Recent developments in deep learning show that event detection algorithms are performing well on sports data [1]; however, they’re […]

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From the following confusion matrix, we can see that the model does a better job at predicting for class 0 than class 1.

Utilizing XGBoost training reports to improve your models

In 2019, AWS unveiled Amazon SageMaker Debugger, a SageMaker capability that enables you to automatically detect a variety of issues that may arise while a model is being trained. SageMaker Debugger captures model state data at specified intervals during a training job. With this data, SageMaker Debugger can detect training issues or anomalies by leveraging […]

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Integrating Amazon Polly with legacy IVR systems by converting output to WAV format

Amazon Web Services (AWS) offers a rich stack of artificial intelligence (AI) and machine learning (ML) services that help automate several components of the customer service industry. Amazon Polly, an AI generated text-to-speech service, enables you to automate and scale your interactive voice solutions, helping to improve productivity and reduce costs. You might face common […]

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Ripley is a Clearpath Robotics Husky equipped with two Universal Robotics UR5 arms.

Introducing Amazon SageMaker Reinforcement Learning Components for open-source Kubeflow pipelines

This blog post was co-authored by AWS and Max Kelsen. Max Kelsen is one of Australia’s leading Artificial Intelligence (AI) and Machine Learning (ML) solutions businesses. The company delivers innovation, directly linked to the generation of business value and competitive advantage to customers in Australia and globally, including Fortune 500 companies. Max Kelsen is also […]

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