https://github.com/nickenshidqia/natural_language_processing_of_books_using_python

Build The Natural Language Processing of Books to analyze books programmatically using Python and extracting valuable insights
https://github.com/nickenshidqia/natural_language_processing_of_books_using_python

natural-language-processing nltk-python python regex stopwords

Last synced: 10 days ago
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Build The Natural Language Processing of Books to analyze books programmatically using Python and extracting valuable insights

• Host: GitHub
• URL: https://github.com/nickenshidqia/natural_language_processing_of_books_using_python
• Owner: nickenshidqia
• Created: 2023-12-28T14:10:59.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-12-28T14:47:16.000Z (about 1 year ago)
• Last Synced: 2024-11-05T21:47:18.269Z (about 2 months ago)
• Topics: natural-language-processing, nltk-python, python, regex, stopwords
• Language: Jupyter Notebook
• Homepage:
• Size: 2.02 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Natural Language Processing of Books Using Python

## Project Description

**Overview :**  

The aim of this project is to leverage Natural Language Processing (NLP) techniques to analyze books programmatically using Python. The project focuses on extracting valuable insights from the text, including the identification of chapters, locating sentences with specific words, determining the most common words, and conducting sentiment analysis to evaluate the emotional tone of each chapter.

**Challenges :**  

Build The Natural Language Processing of Books Using Python.

## Project Goal

The project aims to analyze books programmatically using Python and extracting valuable insights.

## Tools & Library Used

[](https://www.python.org/)  

## Project Result

[Click here to get full code](https://github.com/nickenshidqia/Natural_Language_Processing_of_Books_Using_Python/blob/917006136bcccfc08a256dbbcbaa768d7648a050/natural_language_processing.ipynb)

### Chapter Extraction:

Implement a script to automatically identify and extract chapters from the book.  



### Word Search:

Develop a functionality to locate sentences or paragraphs containing a specific word or phrase.  

Example :  

Which are the sentences where "love" was used?  

  



### Most Common Words :

Utilize NLP libraries to analyze the frequency of words in the book.  



### Sentiment Analysis:

Employ sentiment analysis tools to assess the emotional tone of each chapter.