Text summarization with Amazon SageMaker and Hugging Face

Favorite In this post, we show you how to implement one of the most downloaded Hugging Face pre-trained models used for text summarization, DistilBART-CNN-12-6, within a Jupyter notebook using Amazon SageMaker and the SageMaker Hugging Face Inference Toolkit. Based on the steps shown in this post, you can try summarizing

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Shared by AWS Machine Learning June 15, 2022

Customize pronunciations using Amazon Polly

Favorite Amazon Polly breathes life into text by converting it into lifelike speech. This empowers developers and businesses to create applications that can converse in real time, thereby offering an enhanced interactive experience. Text-to-speech (TTS) in Amazon Polly supports a variety of languages and locales, which enables you to perform

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Shared by AWS Machine Learning June 15, 2022

Extract insights from SAP ERP with no-code ML solutions with Amazon AppFlow and Amazon SageMaker Canvas

Favorite Customers in industries like consumer packaged goods, manufacturing, and retail are always looking for ways to empower their operational processes by enriching them with insights and analytics generated from data. Tasks like sales forecasting directly affect operations such as raw material planning, procurement, manufacturing, distribution, and inbound/outbound logistics, and

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Shared by AWS Machine Learning June 15, 2022

Create, train, and deploy a billion-parameter language model on terabytes of data with TensorFlow and Amazon SageMaker

Favorite The increasing size of language models has been one of the biggest trends in natural language processing (NLP) in recent years. Since 2018, we’ve seen unprecedented development and deployment of ever-larger language models, including BERT and its variants, GPT-2, T-NLG, and GPT-3 (175 billion parameters). These models have pushed

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Shared by AWS Machine Learning June 14, 2022

Enable business analysts to access Amazon SageMaker Canvas without using the AWS Management Console with AWS SSO

Favorite IT has evolved in recent years: thanks to low-code and no-code (LCNC) technologies, an increasing number of people with varying backgrounds require access to tools and platforms that were previously a prerogative to more tech-savvy individuals in the company, such as engineers or developers. Out of those LCNC technologies,

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Shared by AWS Machine Learning June 14, 2022