Data repository for pretrained NLP models and NLP corpora.

Compute Sentence Embeddings Fast!

Train a Word2Vec model or LSA model, and Implement Conceptual Search\Semantic Search in Solr\Lucene - Simon Hughes Dice.com, Dice Tech Jobs

A text analyzer which is based on machine learning,statistics and dictionaries that can analyze text. So far, it supports hot word extracting, text classification, part of speech tagging, named entity recognition, chinese word segment, extracting address, synonym, text clustering, word2vec model, edit distance, chinese word segment, sentence sim…

Go library for performing computations in word2vec binary models

word2vec++ is a Distributed Representations of Words (word2vec) library and tools implementation, written in C++11 from the scratch

基于Word2Vec+SVM对电商的评论数据进行情感分析

vulnerability detection in python source code with LSTM networks

Sentiment Analysis for Arabic Text (tweets, reviews, and standard Arabic) using word2vec

Python library that classifies content from scientific papers with the topics of the Computer Science Ontology (CSO).

A resume filtering based on natural language processing

Word2Vec models with Twitter data using Spark. Blog:

🎓 Open knowledge mining and graph builder

🔤 Calculate average word embeddings (word2vec) from documents for transfer learning

Word2Vec model trained across 640k+ materials science journal articles

Python CLI to apply word2vec to all sorts of text documents.

Dutch word embeddings, trained on a large collection of Dutch social media messages and news/blog/forum posts.

Word2Vec 400M Tweets Embedding model based on https://www.fredericgodin.com/software/

Ready to use Spanish Word2Vec embeddings created from >18B chars and >3B words

How are words loaded with meaning? Repository accompanying research by Alina Arseniev-Koehler and Jacob G. Foster, titled "Machine learning as a model for cultural learning: teaching an algorithm what it means to be fat." https://journals.sagepub.com/doi/full/10.1177/00491241221122603