Project Implementation

Let's build a customer churn prediction model from scratch.

Step 1: Load and Explore Data

Step 2: Prepare Features

Step 3: Split and Scale

Step 4: Train Model

Step 5: Evaluate

Congratulations!

You've built a complete ML pipeline:

• Loaded and explored data
• Engineered and prepared features
• Split and scaled data properly
• Trained a classification model
• Evaluated with appropriate metrics

This is exactly what real data scientists do!