I will build ml models for classification, clustering and prediction in python
ML developer
About this Gig
I'll build, train, and evaluate machine learning models tailored to your problem: classification, regression, or anomaly detection.
I've built and deployed real-world ML systems, including a fraud detection model (Random Forest + SMOTE, 88% recall) and an ECG anomaly detector (XGBoost + PCA).
What you get:
- Data preprocessing and feature engineering
- Model training (Random Forest, XGBoost, Decision Trees, etc.)
- Model evaluation with proper metrics (accuracy, precision/recall, confusion matrix)
- Clean, commented Python code
- Brief explanation of results and model performance
Great for: predicting customer churn, detecting fraud or anomalies, sentiment classification, sales forecasting, and similar structured-data problems.
I'm an ML/Data Science student with hands-on experience turning messy data into working, deployed models.
Message me before ordering to discuss your dataset and goals happy to advise on the right approach first.
Programming language:
Python
Frameworks:
Scikit-learn
•
Keras
Tools:
Jupyter Notebook

