Topic Modelling for Humans
- gensim
- topic-modeling
- information-retrieval
- machine-learning
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Topic Modelling for Humans
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Unsupervised text tokenizer for Neural Network-based text generation.
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.
Translated"Jieba" (Chinese for "to stutter") Chinese text segmentation: built to be the best PHP Chinese word segmentation module.
Fast vectorization, topic modeling, distances and GloVe word embeddings in R.
🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models.
A Modern C++ Data Sciences Toolkit
A collection of languages stemmers and stopwords for Lunr Javascript library
Natural Language Processing (NLP) library for Crystal
Convert a number to an approximated text expression: from '0.23' to 'less than a quarter'.
A Ruby natural language processor.
Fast Porter stemmer implementation
A Go port of the Rapid Automatic Keyword Extraction algorithm (RAKE)
Nickel extracts date, time, and message information from naturally worded text.
Lemmatizer for text in English. Inspired by Python's nltk.corpus.reader.wordnet.morphy
javascript implementation of the popular snowball word stemming nlp algorithm
A Multilingual Latent Dirichlet Allocation (LDA) Pipeline with Stop Words Removal, n-gram features, and Inverse Stemming, in Python.
Word Stemming in Go
Project for filtering stopwords
Gibran is an Elixir natural language processor, and a port of WordsCounted.
Chinese word splitting algorithm MMSEG in GO
Beagle helps you identify keywords, phrases, regexes, and complex search queries of interest in streams of text documents.
Tagify produces a set of tags from a given source. Source can be either an HTML page, a Markdown document or a plain text. Supports English, Russian, Chinese, Hindi, Spanish, Arabic, Japanese, German, Hebrew, French and Korean languages.