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How natural language processing transformers can provide BERT-based sentiment classification on March Madness

SAS Software

SAS' Ali Dixon and Mary Osborne reveal why a BERT-based classifier is now part of our natural language processing capabilities of SAS Viya. The post How natural language processing transformers can provide BERT-based sentiment classification on March Madness appeared first on SAS Blogs.

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Lexalytics Celebrates Its Anniversary: 20 Years of NLP Innovation

Lexalytics

We’ve pioneered a number of industry firsts, including the first commercial sentiment analysis engine, the first Twitter/microblog-specific text analytics in 2010, the first semantic understanding based on Wikipedia in 2011, and the first unsupervised machine learning model for syntax analysis in 2014.

NLP 98
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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. The base model of BERT [ 103 ] had 12 (!) And what’s more, Google made BERT publicly available, so that everyone could have access to contextual word vectors.

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Using Machine Learning for Sentiment Analysis: a Deep Dive

DataRobot Blog

It could be anything from a sentence to a paragraph to a longer-form collection of text. Analytically, we define the tf-idf of a term t as seen in document d , which is a member of a set of documents D as: tfidf( t, d, D ) = tf( t, d ) * idf( t, d, D ). We use the term “document” loosely.)