Favorite The fields of natural language processing (NLP), natural language understanding (NLU), and related branches of machine learning (ML) for text analysis have rapidly evolved to address use cases involving text classification, summarization, translation, and more. State-of-the art, general-purpose architectures such as transformers are making this evolution possible. Looking at

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Shared by AWS Machine Learning November 10, 2021

Favorite Eastern Australia is among the most fire-prone regions in the world. Although bushfires are a regular occurrence in Australia, the 2019–2020 bushfire crisis set ablaze over 17 million hectares of land (larger than the size of England), costing the Australian economy more than $100 billion between property, infrastructure, social,

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Shared by AWS Machine Learning November 10, 2021

Favorite Machine learning (ML) and deep learning (DL) are becoming effective tools for solving diverse computing problems, from image classification in medical diagnosis, conversational AI in chatbots, to recommender systems in ecommerce. However, ML models that have specific latency or high throughput requirements can become prohibitively expensive to run at

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Shared by AWS Machine Learning November 10, 2021

Favorite Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra reimagines enterprise search for your websites and applications so your employees and customers can easily find the content they’re looking for, even when it’s scattered across multiple locations and content repositories within your organization. With

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Shared by AWS Machine Learning November 9, 2021

Favorite AutoGluon-Tabular is an open-source AutoML framework that requires only a single line of Python to train highly accurate machine learning (ML) models on an unprocessed tabular dataset. In this post, we walk you through a way of using AutoGluon-Tabular as a code-free AWS Marketplace product. We use this process

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Shared by AWS Machine Learning November 9, 2021

Favorite Domestic infrastructure issues are a pain for everyone involved. Not only does it negatively affect customer satisfaction, it also has a cascading effect on businesses and their bottom line in terms of financials. Electric utility poles, for example, are an example of a cumbersome infrastructure issue to resolve. Normally,

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Shared by AWS Machine Learning November 9, 2021

Favorite After the article in Nature about the open-source of AlphaFold v2.0 on GitHub by DeepMind, many in the scientific and research community have wanted to try out DeepMind’s AlphaFold implementation firsthand. With compute resources through Amazon Elastic Compute Cloud (Amazon EC2) with Nvidia GPU, you can quickly get AlphaFold

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Shared by AWS Machine Learning November 6, 2021

Favorite Out-of-stock (OOS) is an essential metric tracked across the retail industry. Brick-and-mortar retailers seek to reduce their costs associated with OOS items, while simultaneously increasing shopper satisfaction without inventory surplus. A product can be OOS in three main ways: Distribution OOS, Store OOS, and Shelf OOS. This post focuses

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Shared by AWS Machine Learning November 3, 2021

Favorite This blog post was co-authored, and includes an introduction, by Aaron Brunko, Senior Vice President, Claims Product at Xactware. Property insurance claims involving the valuation and replacement of personal belongings can be a painful process for everyone involved after a loss. From catastrophic events such as hurricanes, tornados, and

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Shared by AWS Machine Learning November 3, 2021

Favorite Today, we’re excited to announce RStudio on Amazon SageMaker, the industry’s first fully-managed RStudio integrated development environment (IDE) in the cloud. You can now bring the current RStudio licenses and migrate your self-managed RStudio environments to Amazon SageMaker in a few simple steps. RStudio is one of the most

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Shared by AWS Machine Learning November 3, 2021