text-preprocessing

Python & Command-line tool to gather text and metadata on the Web: Crawling, scraping, extraction, output as CSV, JSON, HTML, MD, TXT, XML

Text preprocessing, representation and visualization from zero to hero.

🧹 Python package for text cleaning

Preprocessing Library for Natural Language Processing

A python package for text preprocessing task in natural language processing.

Text preprocessing, representation, similarity calculation, text search and classification. Let's go and play with text!

This python module is an easy-to-use port of the text normalization used in the paper "Not low-resource anymore: Aligner ensembling, batch filtering, and new datasets for Bengali-English machine translation". It is intended to be used for normalizing / cleaning Bengali and English text.

Tensor Extraction of Latent Features (T-ELF). Within T-ELF's arsenal are non-negative matrix and tensor factorization solutions, equipped with automatic model determination (also known as the estimation of latent factors - rank) for accurate data modeling. Our software suite encompasses cutting-edge data pre-processing and post-processing modules.

Easy NLP in Python

Text Preprocessing in Python

A powerful text cleaner for Japanese web texts

Extreme Extractive Text Summarization and Topic Modeling (using LSA and LDA techniques) over Reddit Posts from TLDRHQ dataset.

Text preprocessing and PII anonymisation for NLP/ML. ONNX NER ensemble, language detection, stopword removal. Built for statistical ML and language models.

Performs tokenization, stemming, lemmatization, index creation, index compression and ranked retrieval of Cranfield documents

End-to-end NLP project with news scraping from major Colombian outlets. Includes preprocessing, topic classification (MLP, SVM, RF), sentiment analysis with BETO, and NER. Features interactive visualizations to explore trends, emotions, and key actors in Colombian media.

A comprehensive set of Jupyter notebooks that take you from NLP fundamentals to advanced techniques. Covers text preprocessing, POS tagging, NER, sentiment analysis (with VADER), text classification, word embeddings, and transformer models like BERT. Built with real-world datasets using NLTK, spaCy, scikit-learn, and Hugging Face Transformers.

Vector Space based Search Engine for Arxiv Research Publications

My 2020 project focusing on NLP - Information Extraction

A tool for extracting chapters from Gutenberg Project Italian raw text e-books. RegEx are used to match chapter headings and extract the text between them.