Abstract

This study shows a face recognition-based attendance system created with Python. It uses machine learning algorithms to boost accuracy and productivity. Old- school attendance methods often needed to be corrected and took a lot of time. This new system changes that by using real- time facial recognition to do the job. The system relies on a mix of Logistic Regression, Support Vector Machines (SVM), and Random Forest classifiers, with a Voting Classifier to make sure it works as well as possible. The team did a lot of work to clean up facial images and fine-tune settings to make the model more accurate. The results show big improvements in managing attendance, with high accuracy and strong performance in different settings. This system offers a solution that can grow with organizations looking to simplify attendance tracking, reduce human mistakes, and make their operations more effective. Key Words: Face recognition, attendance system, machine learning, real-time application, Voting Classifier, Python.

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