🦆 Contextually-keyed word vectors
Amazon SageMaker Local Mode Examples
Using pre trained word embeddings (Fasttext, Word2Vec)
Incremental learning of word embeddings with context informativeness.
A resume filtering based on natural language processing
Wikidata embedding
NLP with NLTK for Sentiment analysis amazon Products Reviews
Text classification with Reuters-21578 datasets using Gensim Word2Vec and Keras LSTM
Ready to use Spanish Word2Vec embeddings created from >18B chars and >3B words
Aspect-Based Sentiment Analysis
Deep Learning notes and practical implementation with Tensorflow and keras. Text Analytics and practical application implementation with NLTK, Spacy and Gensim.
Creating word embeddings from scratch and visualize them on TensorBoard. Using trained embeddings in Keras.
A simple web application for searching Word2Vec embeddings derived from approximately 2,000 law reports published by the The Incorporated Council of Law Reporting for England & Wales (https://www.iclr.co.uk).
Twitter Sentiment Analysis with Gensim Word2Vec and Keras Convolutional Network
Sentiment analysis for Twitter's tweet (in Indonesia language) was built with 3 models to get a comparison in determining which model gives the best results for predicting a tweet to have a positive or negative meaning.
Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM Network
ArWordVec is a collection of pre-trained word embedding model built from huge repository of Arabic tweets in different topics. The aim of these models is to support the community in their Arabic NLP-based research.
Ensemble PhoBERT with FastText Embedding to improve performance on Vietnamese Sentiment Analysis tasks.
Code to run LDA algorithm on Twitter/Foursquare scraped data.
📷 Crawl and Analyze Instagram Hashtag Data: KoNLPY to gensim word2Vec & scikit-learn TF-IDF
Add a description, image, and links to the gensim-word2vec topic page so that developers can more easily learn about it.
To associate your repository with the gensim-word2vec topic, visit your repo's landing page and select "manage topics."