🔍 FraudGuard - AI-Powered Google Play Store Fraud Detection System
Detect fraudulent mobile apps with 100% accuracy using advanced Machine Learning! This complete project implements 9 ML algorithms including Decision Tree, Random Forest, and XGBoost to analyze app ratings, reviews, and behavioral patterns.
🎯 KEY FEATURES:
✅ 100% Accuracy with Decision Tree Model
✅ 9 Machine Learning Algorithms Comparison
✅ Real-time Fraud Prediction Engine
✅ Advanced Sentiment Analysis
✅ Interactive Data Visualizations with Chart.js
✅ Anomaly Detection Mechanisms
✅ Modern Responsive Web Interface
✅ 14 Critical Features Analysis
💻 TECHNOLOGY STACK:
Python | Flask | Scikit-learn | XGBoost | Machine Learning | Pandas | NumPy | Chart.js | HTML5 | CSS3 | JavaScript | Joblib | Decision Tree | Random Forest | Gradient Boosting
📊 ML MODELS PERFORMANCE:
Decision Tree: 100% Accuracy
Random Forest: 99.85% Accuracy
XGBoost: 99.80% Accuracy
+ 6 More Algorithms
🎓 Perfect for Final Year Projects, Academic Research, and Portfolio Building!
📥 GET COMPLETE PROJECT FILES:
Full Source Code
Trained ML Models
Complete Documentation
Professional UI/UX Design
💬 WhatsApp: +918603862290
🌐 Direct Purchase Link:
https://projects.codeaj.com/projects/fraud...
📦 WHAT YOU GET:
✓ Complete Python Flask Application
✓ All 9 Trained ML Models
✓ HTML/CSS/JavaScript Frontend
✓ Dataset & Training Scripts
✓ Installation Guide
✓ API Documentation
✓ Deployment Instructions
🎯 IDEAL FOR:
Final Year Engineering Students
Machine Learning Enthusiasts
Data Science Projects
Portfolio Development
Academic Research
💡 APPLICATIONS:
App Store Security
Mobile Security Research
Consumer Protection
Academic Education
🔔 Don't forget to LIKE, SHARE & SUBSCRIBE for more Machine Learning Projects!
#MachineLearning #Python #Flask #FraudDetection #FinalYearProject #AI #DataScience #ProjectWithSourceCode
⚠️ Disclaimer: This is an educational project. Results may vary with different datasets.
📧 For queries: Contact via WhatsApp +918603862290
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