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OCTIS

MIND-Lab / OCTIS

Star 789

OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

nlp natural-language-processing hyperparameter-optimization topic-modeling nlp-library bayesian-optimization hyperparameter-tuning latent-dirichlet-allocation evaluation-metrics neural-topic-models latent-semantic-analysis topic-models hyperparameter-search non-negative-matrix-factorization nlproc
  • Updated Jul 25, 2024
  • Python
machine-learning

je-suis-tm / machine-learning

Star 258

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, F…

naive-bayes expectation-maximization support-vector-machine ridge-regression expectation-maximization-algorithm factor-analysis dbscan em-algorithm linear-discriminant-analysis stochastic-gradient-descent latent-semantic-analysis lasso-regression multinomial-naive-bayes singular-value-decomposition batch-gradient-descent sequential-minimal-optimization newton-method low-rank-approximation independent-component-analysis k-nearest-neighbors
  • Updated Dec 16, 2022
  • Jupyter Notebook

jonaschn / awesome-topic-models

Star 98

✨ Awesome - A curated list of amazing Topic Models (implementations, libraries, and resources)

nlp text-mining awesome topic-modeling awesome-list latent-dirichlet-allocation dirichlet-process-mixtures latent-semantic-analysis topic-models non-negative-matrix-factorization dynamic-topic-modeling sentence-lda dirichlet-multinomial topic-model truncated-svd hierarchical-dirichlet-processes labeled-lda author-topic-model
  • Updated Jul 11, 2022

Tuhin-SnapD / Text-Summarization-Models

Star 11

This repository contains various models for text summarization tasks. Each model has a separate directory containing the implementation code, pretrained weights, and a Jupyter notebook for testing the model on sample input texts. Feel free to use these models for your own text summarization tasks or to experiment with them further.

cluster textrank transformer nltk deep-learning-algorithms bart summarization gensim sumy pegasus tfidf bert luhn-algorithm latent-semantic-analysis lexrank sumbasic gpt-2 t5 graph-summarization sentence-ranking
  • Updated Aug 25, 2025
  • Jupyter Notebook

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