XGBoost Home Regressor
Used Python to extract, clean, and apply machine learning to predict housing prices.
- Problem: Estimate home prices based on complex market features.
- Approach: Data cleaning, feature engineering, and XGBoost regression model.
- Outcome: Achieved strong predictive accuracy and feature insights for key housing factors.
Python
XGBoost
Regression
Job Salary Predictions
Used Python to clean job market data and build regression models to predict salaries.
- Problem: People are often under paid. How do I know how much I should be paid?
- Approach: Cleaned a large dataset, then used Linear Regression to predict how much salary should be.
- Insight: Strong features in experience level and company size; produced interpretable salary trends.
Python
Pandas
Regression
Supplier Analysis
Analyzed revenue by supplier, lead times, and the tie between delivery speed and financial performance.
- Problem: Identify top suppliers and bottlenecks across the chain.
- Approach: Exploratory data analysis with SQL/Python; feature pivots and visualizations.
- Insight: Clear pattern between on-time delivery and higher revenue share.
Python
SQL
Supply Chain