Building a custom classifier using Amazon Comprehend

Favorite Amazon Comprehend is a natural language processing (NLP) service that uses machine learning (ML) to find insights and relationships in texts. Amazon Comprehend identifies the language of the text; extracts key phrases, places, people, brands, or events; and understands how positive or negative the text is. For more information

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Shared by AWS Machine Learning December 25, 2019

Amazon Textract becomes PCI DSS certified, and retrieves even more data from tables and forms

Favorite Amazon Textract automatically extracts text and data from scanned documents, and goes beyond simple optical character recognition (OCR) to also identify the contents of fields and information in tables, without templates, configuration, or machine learning experience required. Customers such as Intuit, PitchBook, Change Healthcare, Alfresco, and more are already

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Shared by AWS Machine Learning December 19, 2019

Running distributed TensorFlow training with Amazon SageMaker

Favorite TensorFlow is an open-source machine learning (ML) library widely used to develop heavy-weight deep neural networks (DNNs) that require distributed training using multiple GPUs across multiple hosts. Amazon SageMaker is a managed service that simplifies the ML workflow, starting with labeling data using active learning, hyperparameter tuning, distributed training

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Shared by AWS Machine Learning December 18, 2019

Auto-segmenting objects when performing semantic segmentation labeling with Amazon SageMaker Ground Truth

Favorite Amazon SageMaker Ground Truth helps you build highly accurate training datasets for machine learning (ML) quickly. Ground Truth offers easy access to third-party and your own human labelers and provides them with built-in workflows and interfaces for common labeling tasks. Additionally, Ground Truth can lower your labeling costs by

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Shared by AWS Machine Learning December 13, 2019