There are 8 repositories under gensim-word2vec topic.
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
Text classification with Reuters-21578 datasets using Gensim Word2Vec and Keras LSTM
NLP with NLTK for Sentiment analysis amazon Products Reviews
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.
Machine Learning Practise
📷 Crawl and Analyze Instagram Hashtag Data: KoNLPY to gensim word2Vec & scikit-learn TF-IDF
A tool to view how Word2Vec represents words in your favourite books.
A web service that exposes semantic similarity search via a web GUI and a RESTful API.
Automnomously attempting a categorical summarization of a sparse, asymmetrical corpus in English language, by performing text classification - which is achieved by our intuitive sentence pair classification scenarios and usecases.
🎓 Diploma Thesis | A Word2vec comparative study of CBOW and Skipgram
BBC News classification algorithm comparison
This repository is a collection of six minor projects focused on Natural Language Processing (NLP) along with relevant datasets. The projects are designed to help individuals gain a better understanding of NLP by applying concepts to real-world problems. Additionally, the repository includes a file that provides a comprehensive overview of NLP .
Visually explore a game of semantle using a UMAP representation of the underlying word2vec word embedding.
Generate and predict text, using Recurrent Neural Networks. (Keras+Tensorflow+Gensim)
This repository is contains the Word2Vec model for Harry Potter series.
A Natural Language Search Enabled for Pharmaceutical research data. We aim to easily and efficiently find any search results using a word2vec encoder
Text classification is the task of assigning a set of predefined categories to free text. Text classifiers can be used to organize, structure, and categorize pretty much anything. For example, new articles can be organized by topics, support tickets can be organized by urgency, chat conversations can be organized by language, brand mentions can be organized by sentiment, and so on.
English Corpus Text-Visualization using Word2Vec Model from Gensim. A mini project under the mentorship of Prof. Sandipan Ganguly, HIT-K.
NLP - Identify authors from their writings