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extract text from any document. no muss. no fuss.
Library to scrape and clean web pages to create massive datasets.
a curated list of R tutorials for Data Science, NLP and Machine Learning
Beautiful visualizations of how language differs among document types.
A curated list of resources dedicated to text summarization
Python package for Korean natural language processing.
A configurable web spider with a easy-to-use web console
Text mining using tidy tools
Manuscript of the book "Tidy Text Mining with R" by Julia Silge and David Robinson
Python implementation of the Rapid Automatic Keyword Extraction algorithm using NLTK.
AutoPhrase: Automated Phrase Mining from Massive Text Corpora
Fast vectorization, topic modeling, distances and GloVe word embeddings in R.
Starter code to solve real world text data problems. Includes: Gensim Word2Vec, phrase embeddings, Text Classification with Logistic Regression, word count with pyspark, simple text preprocessing, pre-trained embeddings and more.
Fast topic modeling platform
R package for web-based interactive topic model visualization.
A collection of notebooks for Natural Language Processing from NLP Town
Repository with all what is necessary for sentiment analysis and related areas
Various Algorithms for Short Text Mining
从新浪财经、每经网、金融界、中国证券网、证券时报网上，爬取上市公司（个股）的历史新闻文本数据进行文本分析、提取特征集，然后利用SVM、随机森林等分类器进行训练，最后对实施抓取的新闻数据进行分类预测
RMDL: Random Multimodel Deep Learning for Classification
Resources for learning about Text Mining and Natural Language Processing
Open Semantic Search Engine and Open Source Text Mining & Text Analytics platform (Integrates ETL for document processing, OCR for images & PDF, named entity recognition for persons, organizations & locations, metadata management by thesaurus & ontologies, search user interface & search apps for fulltext search, faceted search & knowledge graph)
Machine Learning Lectures at the European Space Agency (ESA) in 2018
This repository contains the code related to Natural Language Processing using python scripting language. All the codes are related to my book entitled "Python Natural Language Processing"
Language, Knowledge, Cognition
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texthero.preprocessing.fillna() only replace the nan with writespace.
It should support customized fill content