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Face Recognition Attendance Project Using Machine Learning

Face Recognition Attendance System Step-by-Step | Real Face Recognition Attendance Project | Face Recognition 2025

Last Updated:05/2026 English (US) Instructor: Eduonix Learning Solutions

Lectures: 9
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Videos: 0 hours
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Level: All
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Language: English
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Last Updated: 05/2026

Skills: Machine Learning Python OpenCV

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About this Course

The Complete Face Recognition Attendance System Using KNN course is a practical, project-based program designed to help learners build a fully functional automated attendance system using Face Recognition technology. In this course, students will learn how to detect, recognize, and verify faces in real time using Python, OpenCV, and the K-Nearest Neighbors (KNN) algorithm. The course covers every stage of development, including data collection, image preprocessing, feature extraction, model training, testing, and attendance management integration. Learners will also explore how to store attendance records securely using CSV files or databases while creating a user-friendly interface for real-world applications. By the end of the course, students will have developed a complete Face Recognition Attendance System suitable for schools, offices, and security-based environments, along with gaining valuable hands-on experience in computer vision and machine learning.

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Eduonix creates and distributes high quality technology training content. Our team of industry professionals have been training manpower for more than a decade. We aim to teach technology the way it is used in industry and professional world. We have professional team of trainers for technologies ranging from Mobility, Web to Enterprise and Database and Server Administration.

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