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Tfidf Python Packages

Python packages with the GitHub topic tfidf. Sorted by relevance, with stars and monthly downloads.
cereja-project
cereja

Cereja is a bundle of useful functions we don't want to rewrite and .. just pure fun!

10K 29 12
PaulMcInnis
jobfunnel

Scrape job websites into a single spreadsheet with no duplicates.

4K 2K 261
AreteDriver
memboot

Zero-infrastructure persistent memory for any LLM

2K 1 1
SauravPattnaikCS60
weighted-class-tfidf

Weighted Class TFIDF technique to deal with imbalanced datasets

764 14 1
andrewtavis
wikirec

Recommendation engine framework based on Wikipedia data

603 20 10
Jash271
youglance

Package for analyzing Youtube Videos from searching by relevant entities to analyzing sentiments and clustering different parts of the video according to your liking

547 1 0
castnettech
mnemosyne-engine

State aware knowledge compression, ingestion, and hybrid retrieval engine. Zero dependencies. Sub-100ms queries.

504 58 9
brunoarine
findlike

Command-line tool that finds lexically similar documents in relation to a reference text file or ad-hoc query

418 16 2
castnettech
mnemosyne-ollama

State aware knowledge compression, ingestion, and hybrid retrieval engine. Zero dependencies. Sub-100ms queries.

403 58 9
andrewtavis
kwx

BERT, LDA, and TFIDF based keyword extraction in Python

342 76 12
daedalus
llm-distiller

Model distiller automator

304 1 0
Jash271
summarizeit

Package for analyzing Youtube Videos from searching by relevant entities to analyzing sentiments and clustering different parts of the video according to your liking

250 1 0
castnettech
mnemosyne-mcp

State aware knowledge compression, ingestion, and hybrid retrieval engine. Zero dependencies. Sub-100ms queries.

217 58 9
parthjain18
sassyshell

A sassy, AI-powered CLI sidekick that remembers the commands you forget and mocks you into getting better.

205 8 3
nikhiljsk
preprocess-nlp

A fast framework for pre-processing (Cleaning text, Reduction of vocabulary, Feature extraction and Vectorization). Implemented with parallel processing using custom number of processes.

198 10 4
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