Machine-Deep-Learning-in-Python-and-R/Machine-Learning-in-R/Natural-Language-Processing/readme at master · dundee2002/Machine-Deep-Learning-in-Python-and-R · GitHub

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End-to-end Natural Language Processing (NLP)
  1. text cleaning: removing puntuations, numbers, stopwords, HTML tags and URLs, stemming
  2. text tokenizing and creating a bag-of-words model

Examples:
  1. UCI Spam Collection data  https://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection
  2. UCI Yelp Restaurant Review data  https://archive.ics.uci.edu/ml/datasets/Sentiment+Labelled+Sentences#
  3. UCI Amazon Product Review data  https://archive.ics.uci.edu/ml/datasets/Sentiment+Labelled+Sentences#
  4. CrowdFlower Twitter Global Warming Sentiment data  https://www.crowdflower.com/data-for-everyone/
  5. CrowdFlower Twitter Airline Sentiment data https://www.crowdflower.com/data-for-everyone/