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Gensim Python Packages

Python packages with the GitHub topic gensim. Sorted by relevance, with stars and monthly downloads.
RaRe-Technologies
gensim

Topic Modelling for Humans

7.1M 16K 4K
explosion
sense2vec

🦆 Contextually-keyed word vectors

3K 2K 236
pandora-intelligence
concise-concepts

This repository contains an easy and intuitive approach to few-shot NER using most similar expansion over spaCy embeddings. Now with entity confidence scores!

791 244 14
eggplants
aovec

Easy aozorabunko Word2Vec Builder - 青空文庫全書籍のWord2Vecビルダー+構築済みモデル

765 3 0
AICoE
log-anomaly-detector

Log Anomaly Detection - Machine learning to detect abnormal events logs

517 346 138
Text-Analysis
srsparser

📑 Semi-structured documents parser using Python and NLP algorithms

458 3 0
SarthakJShetty
pyresearchinsights

End-to-end tool for scientific literature analysis

339 32 10
hechmik
word-mover-distance

Compute Word Mover's Distance using any type of Word Embedding model

284 9 0
banjtheman
topicblob

Text to Topics

259 3 5
cordelia-io
centroid-summarizer

Extractive text summarization using centroid distance

258 1 1
pelican-plugins
pelican-similar-posts

Pelican plugin to add similar posts to articles, based on a vector space model

240 20 3
giacbrd
shallowlearn

An experiment about re-implementing supervised learning models based on shallow neural network approaches (e.g. fastText) with some additional exclusive features and nice API. Written in Python and fully compatible with Scikit-learn.

211 198 29
Rickecr
pyelit

Extraction of Locations and Issues of a Text

206 4 2
autonomio
signs

Signs Text Processing for Deep Learning

178 13 3
bees4ever
seaqube

Semantic Quality Benchmark for Word Embeddings, i.e. Natural Language Models in Python. Acronym `SeaQuBe` or `seaqube`.

170 3 0
Rochan-A
sptm

Sentence Topic Prediction using Topic Modeling

146 6 3
js1010
cusim

cusim

145 45 9
ayushsubedi
choto

A CLI tool that summarizes news and articles.

107 2 2
Christoph
robics

Automatic detection of robust parametrizations for LDA and NMF. Compatible with scikit-learn and gensim.

98 3 0
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