Popular GitHub Repositories for Latent Dirichlet Allocation

Python package of Tomoto, the Topic Modeling Tool

Topic modelling on financial news with Natural Language Processing

Use Python and NLTK to build out your own text classifiers and solve common NLP problems

Library of Joint Topic-Sentiment Models

Inferring Concept Prerequisite Relations from Online Educational Resources (IAAI-19)

My version of topic modelling using Latent Dirichlet Allocation (LDA) which finds the best number of topics for a set of documents using ldatuning package which comes with different metrics

Machine Learning and Natural Language Processing of the EEA Corpus via spaCy, Textacy and pyLDAvis and other useful NLP algorithms.

Sentiment Analysis of Twitter Data (saotd)

Analyzing Google Play Store reviews of the Indonesian streaming platform Vidio through topic modeling with the assistance of GPT.

Project to develop a recommendation system for scientific papers using databases and unsupervised topic models

IMDB Movie Reviews - Text preprocessing and classification. Includes BOW model, TF_IDF, VADER entiment analysis, Topic Modelling using Latent Dirichlet Allocation and Word Embeddings. (Python)

Build intelligent applications that can interpret the human language to deliver impactful results

TuoTuo is a Topic Modeling library for Researchers and Engineers

Topic Modeling using Gensim and spaCy

Cythonized implementation of Topic modeling.

Temporal analysis of legal texts via topic modelling and temporal word embeddings

Learning Latent Semantic Representations of Paintings for Personalized Recommendation

Building a recommendation system for Google Play games using content-based and collaborative filtering models

Multi-pronged, multi-stage analysis of a 3.5M-sentences science fiction corpus using optimized NLP, with NER techniques, LDA modeling and LLM integration. After final commit, will be able to run a main file to generate a visualization of results on-demand. Modularized and documented code that can easily be reused/refitted for other kinds of corpii.

Cluster documents and extract global and local topics per cluster using LDA (Latent Dirichlet Allocation) algorithm