This project showcases a complete real-world data science pipeline using simulated datasets. It walks through every major stage of the ML workflow — Data Cleaning, Exploratory Data Analysis (EDA), Feature Engineering, and Model Evaluation — following best practices used by professional data scientists.
Whether you're preparing for interviews or building a solid portfolio, this project will help you understand how real data is handled, insights are generated, and models are built and evaluated properly.
✅ Clean messy data
📊 Explore insights visually and statistically
🧱 Engineer powerful features
🎯 Evaluate models with all real-world metrics
- Class Imbalance