📌 Credit Risk Prediction Using Machine Learning & Neural Networks | Model Optimization & Comparison скачать в хорошем качестве

📌 Credit Risk Prediction Using Machine Learning & Neural Networks | Model Optimization & Comparison

🚀 In this video, I walk through my Credit Risk Prediction project, where I implement and compare Machine Learning and Neural Network models to classify loan applicants as low-risk or high-risk. 🔍 What’s Covered in This Video? ✅ Problem Statement & Dataset Overview 📊 ✅ Implementation of ML Models (Logistic Regression, SVM, XGBoost) ✅ Neural Network Models (Basic & Optimized) ✅ Optimization Techniques (Adam, RMSprop, L1/L2 Regularization, Dropout) ✅ Performance Comparison & Best Model Selection ✅ Confusion Matrix & Error Analysis ✅ Key Findings & Future Improvements 📌 Best Model: The optimized Neural Network with Adam optimizer & L2 regularization achieved 90% accuracy, outperforming classical ML models! 🎯 Next Steps: Test on real-world financial data Deploy as an API for credit risk assessment