Lexalytics

JULY 12, 2023

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

NLP Natural Language Processing Text Analytics BERT 98

Lexalytics

APRIL 5, 2021

This is the sort of representation that is useful for natural language processing. ELMo would also be the first of the Muppet-themed language models that would come to include ERNIE [ 120 ], Grover [ 121 ]….and The base model of BERT [ 103 ] had 12 (!) layers of bidirectional Transformers.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

AWS Machine Learning Blog

OCTOBER 23, 2023

Founded in 2011, Talent.com is one of the world’s largest sources of employment. With over 30 million jobs listed in more than 75 countries, Talent.com serves jobs across many languages, industries, and distribution channels. The two sets are standard feature engineering and fine-tuned Sentence-BERT (SBERT) embeddings.

NLP 107

NLP Deep Learning Machine Learning Natural Language Processing 107

Sebastian Ruder

NOVEMBER 14, 2022

Models that allow interaction via natural language have become ubiquitious. Research models such as BERT and T5 have become much more accessible while the latest generation of language and multi-modal models are demonstrating increasingly powerful capabilities. On Achieving and Evaluating Language-Independence in NLP.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

Sebastian Ruder

OCTOBER 26, 2019

In particular, I cover unsupervised deep multilingual models such as multilingual BERT. Cross-lingual learning in the transfer learning taxonomy ( Ruder, 2019 ) Methods from domain adaptation have also been applied to cross-lingual transfer ( Prettenhofer & Stein, 2011 , Wan et al., 2019 ; Wu & Dredze, 2019 ). 2019 ; Wu et al.,

BERT 52

BERT NLP Neural Network Natural Language Processing 52

Sebastian Ruder

DECEMBER 6, 2021

Reading Comprehension assumes a gold paragraph is provided Standard approaches for reading comprehension build on pre-trained models such as BERT. Using BERT for reading comprehension involves fine-tuning it to predict a) whether a question is answerable and b) whether each token is the start and end of an answer span.

BERT 52

BERT NLP Natural Language Processing Computational Linguistics 52

Explosion

MARCH 17, 2019

of the spaCy Natural Language Processing library includes a huge number of features, improvements and bug fixes. spaCy is an open-source library for industrial-strength natural language processing in Python. Clearly, we couldn’t use a model such as BERT or GPT-2 directly. Version 2.1

NLP 52

NLP Python Neural Network Natural Language Processing 52