Project Details
Project information
- Category: Machine Learning
- Developed For: Social Media Security Enhancement
- Project date: June 2024
Spammer Detection and Fake User Identification on Social Networks
Developed a machine learning-based system to detect spam messages and identify fake users leveraging the Random Forest Classifier. The system analyzes user-generated content on social media platforms to flag potential spam accounts and fake profiles. By implementing this model, social media platforms can enhance user trust and maintain high content quality. The project achieved a 92% accuracy rate and was integrated with a live server, providing real-time detection and a user-friendly front-end interface.
Project information
- Category: Database Management
- Developed For: Web Application Efficiency
- Project date: November 2023
User Management System
Designed and implemented a user management system using Java, JDBC, and Servlet technology in Eclipse IDE. The system manages user registration, authentication, and profile handling with secure session tracking. It is ideal for web applications requiring efficient user data management. The project focused on improving server performance by streamlining data operations and minimizing errors. This system ensures smooth user interactions and reliable backend operations.
Project information
- Category: Predictive Analytics
- Developed For: Price Forecasting
- Project date: June 2023
Electric Price Prediction Model
A predictive model for forecasting electricity prices using Python and machine learning in Jupyter Notebook. The model analyzes historical data to provide accurate predictions, helping utility companies optimize pricing strategies and resource allocation. It incorporates advanced algorithms to enhance forecasting accuracy. The project offers practical insights for operational planning in the energy sector. Its results contribute to more efficient decision-making processes for energy providers.