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aimaster-dev / default_loan_prediction

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This project automates bank credit risk assessment using AI and machine learning models to predict loan defaults. It streamlines the credit process with predictive analytics, model evaluation, explainability (SHAP), and deployment readiness.

flask finance automation vuejs sklearn fintech xgboost classification lightgbm banking-applications fraud-detection roc-auc credit-risk loan-prediction-analysis shap explainability model-interpretability loan-prediction
  • Updated May 29, 2025
  • JavaScript

dyneth02 / Genome-based-Disorder-Prediction-System

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Machine learning system for predicting genetic disorders using genomic, clinical, and demographic data. Implements robust preprocessing, feature selection, and multi-model classification (RF, XGBoost, LightGBM, CatBoost) with cross-validation to support early, data-driven genetic risk assessment.

machine-learning data-mining bioinformatics genomics random-forest xgboost lightgbm ensemble-learning academic-project data-preprocessing feature-engineering predictive-modeling imbalanced-data model-evaluation precision-medicine catboost applied-data-science classification-models medical-ai healthcare-analytics
  • Updated Jan 2, 2026
  • JavaScript

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