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Healthcare NLP 5.0.2 announcement

John Snow Labs

We are delighted to announce a suite of remarkable enhancements and updates in our latest release of Healthcare NLP. With a strong ability to thoroughly analyze text, these models categorize content into No_Transportation_Insecurity_Or_Unknown and Transportation_Insecurity , providing valuable insights into transportation-related insecurity.

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NLP Lab 4.10 Introduces In-App Trial License Generation, Enhanced Commenting and Tagging Capabilities, and Improved Task Export Filters

John Snow Labs

We are thrilled to announce the release of NLP Lab 4.10, which comes with an array of exciting new features aimed at enhancing user experience and improving the efficiency of the platform. Comments on the Labeling Page NLP Lab 4.10 Tags definition on the Labeling Screen NLP Lab 4.10 Filters for exporting tasks NLP Lab 4.10

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Discovering climate change impact with Snorkel-enabled NLP

Snorkel AI

Prasanna Balaprakash, research and development lead from Argonne National Laboratory gave a presentation entitled “Extracting the Impact of Climate Change from Scientific Literature using Snorkel-Enabled NLP” at Snorkel AI’s Future of Data-Centric AI Workshop in August, 2022. You group the critical infrastructures into various classes.

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Discovering climate change impact with Snorkel-enabled NLP

Snorkel AI

Prasanna Balaprakash, research and development lead from Argonne National Laboratory gave a presentation entitled “Extracting the Impact of Climate Change from Scientific Literature using Snorkel-Enabled NLP” at Snorkel AI’s Future of Data-Centric AI Workshop in August, 2022. You group the critical infrastructures into various classes.

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Build an automated insight extraction framework for customer feedback analysis with Amazon Bedrock and Amazon QuickSight

AWS Machine Learning Blog

Manually analyzing and categorizing large volumes of unstructured data, such as reviews, comments, and emails, is a time-consuming process prone to inconsistencies and subjectivity. By using the pre-trained knowledge of LLMs, zero-shot and few-shot approaches enable models to perform NLP with minimal or no labeled data.

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What is Pattern Recognition? A Gentle Introduction (2025)

Viso.ai

The identification of regularities in data can then be used to make predictions, categorize information, and improve decision-making processes. While explorative pattern recognition aims to identify data patterns in general, descriptive pattern recognition starts by categorizing the detected patterns.

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Applied NLP Thinking: How to Translate Problems into Solutions

Explosion

In this blog post, I’m going to discuss some of the biggest challenges for applied NLP and translating business problems into machine learning solutions. This blog post is based on talks I gave at the “Teaching NLP” workshop at NAACL 2021 and the L3-AI online conference. I call this “Applied NLP Thinking”. So where do you start?

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