The Skill Set Recommender System is an open-source platform tailored to simplify the candidate recommendation process. It uses machine learning-inspired similarity algorithms to compare user-defined skill requirements with a dataset of candidates, generating ranked suggestions based on compatibility. Key features include:
- Interactive User Interface: Built with Bootstrap for responsive and intuitive interactions.
- Backend Intelligence: Powered by Flask, offering both web and API-based recommendations.
- Advanced Algorithms: Employs Euclidean distance and Pearson correlation to ensure accurate matches.
- Extensive Dataset: Preloaded with diverse candidate profiles for robust testing and demonstrations.
Explore, fork, and contribute to this project to enhance its capabilities and adapt it to your needs!