Initial release

This is the initial release of the project, which includes the following features and components:

Features:

• Implemented data extraction from the freeCodeCamp GitHub repository.
• Processed and preprocessed data using various feature selection and engineering techniques.
• Developed a Random Forest classifier for predicting issue resolution times.
• Implemented a Large Language Model (LLM) for issue type classification.
• Evaluated model performance using F-score, recall, and precision metrics.
• Analyzed and improved model accuracy through parameter tuning and feature correlation analysis.

Installation Instructions:

1. Install the required dependencies:
   pip install -r requirements.txt

Usage:

• Follow the steps in the text_data.ipynb notebook to process text data and train the LLM.
• Follow the steps in the non_text_data.ipynb notebook to process non-text data and train the Random Forest classifier.

Acknowledgments:

• Special thanks to the contributors of the freeCodeCamp repository and the open-source community for their support and resources.