This project implements a machine learning model to score and suggest improvements for resumes. The model evaluates resumes based on a dataset of resumes and generates suggestions for enhancing their quality. The system works by processing PDF resumes and scoring them based on various features such as formatting, content relevance, and overall readability.
- Resume Scoring: Automatically assigns a score to resumes based on their quality.
- Suggestions: Provides actionable suggestions to improve the resume, such as enhancing content or reformatting sections.
- PDF Input: Accepts resumes in PDF format for analysis.
- CSV Dataset: Uses a CSV dataset of resumes for model training and evaluation.
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Clone the repository:
git clone https://github.com/yourusername/resume-scoring-suggestion-model.git cd resume-scoring-suggestion-model -
Install the required libraries:
pip install -r requirements.txt pip install PyPDF2