Understanding NLP Pipeline

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Natural Language Processing Wordcloud (Source: Wootric)

This repository contains examples for stages in Natural Language Processing (NLP) Pipeline. The NLP Pipeline involves the following stages.

1. Text Processing
   • Cleaning
   • Normalization
   • Tokenization
   • Stop Word Removal
   • Part of Speech Tagging
   • Named Entity Recognition
   • Stemming and Lemmatization
2. Feature Extraction
   • Bag of Words
   • TF-IDF
   • One-hot Encoding
   • Word Embeddings
3. Modeling

Natural Language Processing Pipeline

Files

• text_processing.ipynb: This file explains the various stages involved in text processing.
  

Stages in Text Processing

• bow_tfidf_example.ipynb: This file contains examples on Bag of Words (BOW) model and Term Frequency — Inverse Document Frequency (TF-IDF) calculation.

• beautiful_soup_example.ipynb: This file contains example showing usage of BeautifulSoup library on crawling data from real estate agents section of realtor.com website

Note: Hope you gained some knowledge reading this article. Please remember that this article is just an overview and my understanding of NLP pipeline that I read from various online sources.

Note: Examples on more stages coming soon