Pre-trained word vectors of 30+ languages

bias analysis with NLP on partisan news portals from argentina

Investigating the similarity of the texts on the uploaded batch of text files

Die Skripte in diesem Repository sind im Rahmen der Dokumentenanalyse (v. a. Topic Modeling) in Kooperation mit Polit-X entstanden.

Реализация командного проекта для "Газпром нефть"

Topic modelling using gensim

A basic word-embedding model to find best matching students or professors, and recommend the top n results to a specific student

Review of Latent Dirichlet Allocation (LDA) for topic extraction of product reviews for use by product managers. Explores high level overview of LDA, popular libraries, and potential improvements to or over LDA for topic extraction of reviews.

Finding keywords in news headlines that affect market sentiment, usng 2 different datasets from Kaggle, combine them, attached price data and running Tfidf_Elastic_net

Python pipeline for topic modeling with LDA: preprocessing, coherence-based topic selection, and interactive visualization.

Machine Learning and NLP project based on zackthoutt's "Wine Reviews" dataset (kaggle.com)

Word2Vec (gensim) trained on english wikipedia

Explore & Discover Research Papers on Arxiv repository using Topics learned using LDA using Gensim

This is a simple text summarizer app using .NET Core, Angular, Python REST API built using Flask REST and summarizer built using Gensim python library

Twitter sentiment analysis with word2vec.

Enhance product classification into market-place categories, through text and image processing.