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Understand Text Mining Using No Code Tool Orange

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Text Mining is also known as Text Data Mining or Text Analytics or is an artificial intelligence (AI) technology that uses natural language processing (NLP) to extract essential data from standard language text.

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NLP Landscape: Switzerland

NLP People

While ETH does not have a Linguistics department, its Data Analytics Lab , lead by Thomas Hofmann , focuses on topics in machine learning, natural language processing and understanding, data mining and information retrieval. Google Zurich employs specialists in fields such as NLP, Linguistics, machine learning and AI.

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NLP Landscape: Germany (Research & Education)

NLP People

Are you looking to study or work in the field of NLP? For this series, NLP People will be taking a closer look at the NLP education & development landscape in different parts of the world, including the best sites for job-seekers and where you can go for the leading NLP-related education programs on offer.

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Leveraging user-generated social media content with text-mining examples

IBM Journey to AI blog

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? Text analysis takes it a step farther by focusing on pattern identification across large datasets, producing more quantitative results.

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Unleashing the Power of Applied Text Mining in Python: Revolutionize Your Data Analysis

Pickl AI

Introduction to Applied Text Mining in Python Before going ahead, it is important to understand, What is Text Mining in Python? Text mining is also known as text analytics or Natural Language Processing (NLP). Frequently Asked Questions How does text mining differ from data mining?

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Dude, Where’s My Neural Net? An Informal and Slightly Personal History

Lexalytics

Fast-forward a couple of decades: I was (and still am) working at Lexalytics, a text-analytics company that has a comprehensive NLP stack developed over many years. As with ULMFiT and ELMo, these contextual word vectors could be incorporated into any NLP application. I was out of the neural net biz. and BERT.