I will build a machine learning model for classification and regression

You have data. You need predictions.

I build production-ready machine learning models in Python, not

toy examples, but real models with proper evaluation, cross-validation,

and a plain-English explanation of what drives the predictions.

WHAT I BUILD

• Classification churn, fraud, credit scoring, diagnosis
• Regression price prediction, demand forecasting, sales estimation
• Multi-class product categorisation, risk tiers
• Ranking & scoring lead scoring, credit scores

WHAT YOU GET

• Trained model file (.pkl) ready to deploy
• Full Jupyter notebook clean and commented
• Evaluation report AUC, F1, Precision, Recall, MCC
• Feature importance: which variables drive predictions
• Business explanation in plain English, not just numbers
• 5-fold cross-validation honest performance estimates

MY APPROACH

I compare multiple algorithms, evaluate all of them honestly,

and recommend the best one with evidence.

Real project: AgroCredit ML System 2,000 farmers, 52 features,

5 models compared. Best result: ROC-AUC = 0.989.

TOOLS

Python · scikit-learn · XGBoost · LightGBM · SHAP · Pandas

Message me with your dataset details before ordering.

I'll confirm the scope and timeline. No surprises.