Muhammad-Elgendi/NLP

Introducing Natural Language Processing (NLP) with jupyter notebooks.

NLP jupyter notebooks

Introducing Natural Language Processing (NLP) with hands-on projects.

Acknowledgements and References

1. Python Refresher

   • This notebook was created by Jose Portilla in his course "Python for Data Science and Machine Learning Bootcamp"

2. Object Oriented Programming (OOP)

   • Chapters 10 and 11 from "Introduction to Java Programming, Comprehensive Version, 10th Edition Book by Y. Daniel Liang"
   • Python 3 - dictionary update() Method - Tutorialspoint
   • Python - Object Oriented - Tutorialspoint
   • Supercharge Your Classes With Python super() – Real Python
   • A.1: Difference between Abstraction and Encapsulation in C++ - Engineering LibreTexts

3. Files and databases handling

   • Python 3 - Files I/O - Tutorialspoint
   • Python 3 - File Methods - Tutorialspoint
   • Database Programming in Python | Basics | Open Source Foru
   • SQLite - Python - Tutorialspoint
   • DB Browser for SQLite

4. Strings and regular expressions

   • Python - Strings - Tutorialspoint
   • Regular Expression HOWTO — Python 3.9.5 documentation

5. Getting Started With NLP

   • Chapter 1 from "Deep Learning for Natural Language Processing Book by Karan Jain, Palash Goyal, and Sumit Pandey"
   • Natural Language Processing Key Terms, Explained - KDnuggets
   • Python Virtual Environments: A Primer – Real Python
   • API Reference — TextBlob 0.16.0 documentation

6. Getting Started With NLP 2

   • Chapter 1 from "Deep Learning for Natural Language Processing Book by Karan Jain, Palash Goyal, and Sumit Pandey"
   • Using Virtual Environments in Jupyter Notebook and Python
   • urllib.request — Extensible library for opening URLs — Python 3.9.5 documentation
   • Requests: HTTP for Humans™ — Requests 2.25.1 documentation
   • Beautiful Soup Documentation — Beautiful Soup 4.9.0 documentation
   • Scrapy | A Fast and Powerful Scraping and Web Crawling Framework
   • sklearn.feature_extraction.text.TfidfVectorizer — scikit-learn 0.24.2 documentation
   • scipy.sparse.csr_matrix — SciPy v1.6.3 Reference Guide

7. Text Vectorization

   • Chapter 4 from "Applied Text Analysis with Python Book by Benjamin Bengfort, Rebecca Bilbro, and Tony Ojeda"
   • Python | yield Keyword - GeeksforGeeks
   • How to Use Generators and yield in Python – Real Python
   • Defaultdict in Python - GeeksforGeeks
   • sklearn.feature_extraction.text.CountVectorizer — scikit-learn 0.24.2 documentation
   • Doc2Vec Model — gensim