Projects
Behavioral Biometric Continuous Authentication ML model
Python, Jupyter Notebook
The model achieved an accuracy of 99.7% and low error rates using 23 features with the Random Forest algorithm.
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Utilized RF, KNN, SVM, LOG, DT, and NB algorithms for model development.
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Utilized feature importance analysis, Persona Correlation, and Mutual Information techniques to optimize feature selection for superior model performance.
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Applied advanced feature visualization methods for model optimization.
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Developed Learning Management System (LMS)
Angular, ASP.NET Core Web API, and Oracle database
Catering to three distinct user types - Admins, Trainers, and Trainees - with tailored functionalities within the LMS:
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Empowering the system to generate Certificates with QR codes.
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Enabling comprehensive reporting and statistical analysis.
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Courses Management, Attendance Management Assessment and Evaluation tools.
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User Authentication.
E-commerce platform
ASP.NET Core MVC, and Oracle database integration.
Catering to two distinct user types - Admin, and Customers - with tailored functionalities within the LMS:
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Implemented features including user registration, authentication, product catalog, shopping cart, order management, payment processing, user reviews and testimonials, search, filtering, reports, statistics, and additional enhancements.
