I will build a fraud detection or classification ml model in python

Are you looking to detect fraud, predict churn, classify customers, or build any binary or multiclass ML model from your data?

I'm a Python ML developer with 5 deployed machine learning projects including a fraud detection system achieving 0.98 ROC-AUC using XGBoost and SHAP explainability.

What I deliver:

• Trained ML model (XGBoost, Random Forest, Logistic Regression best fit for your data)
• Full evaluation report (accuracy, precision, recall, F1, ROC-AUC)
• SHAP feature importance charts so you understand why the model predicts what it does
• Clean, commented Python code you can run and modify
• Optional Streamlit dashboard to visualize results interactively

I work with:

• Tabular data (CSV, Excel, SQL exports)
• Imbalanced datasets (SMOTE, class weighting)
• Any classification problem fraud, churn, default risk, spam, medical diagnosis

My portfolio includes:

• Fraud Detection System 0.98 ROC-AUC, XGBoost + SHAP
• Loan Default Risk Engine 1.3M+ records
• AI Bankruptcy Risk Analyzer

Message me before ordering if you're unsure whether your project fits I'll tell you honestly.