This is a Python program that reads text from a PDF file and applies unsupervised learning to understand the text. The program uses topic modeling to identify the main topics of the text and can answer questions related to the text.

• Installation
• Usage
• Examples
• Contributing
• License

To use this program, you will need to have Python 3.x installed on your computer. You can download Python from the official website: https://www.python.org/downloads/

You will also need to install the following Python packages:

• PyPDF2
• nltk
• scikit-learn

To use the program, follow these steps:

1. Download the program files to your computer
2. Open a command prompt or terminal window
3. Navigate to the directory where the program files are located
4. Type the following command to run the program:
   python reader.py
5. Follow the on-screen instructions to enter the name of the PDF file and ask questions related to the text

Here are some examples of questions you can ask the program:

• "What is the main topic of the text?"
• "How many pages does the text have?"
• "What are the subtopics discussed in the text?"
• "Who is the author of the text?"
• "What is the text about?"

If you would like to contribute to this project, please fork the repository and make changes as you see fit. When you are ready to submit a pull request, please ensure that your code follows the PEP 8 style guide and has been tested on your local machine.

This project is licensed under the MIT License. See the LICENSE file for more details.