Summary — The Full Workflow at a Glance
Step | Phase | What You Did | Business Value |
1. Data Collection | Data Analysis | Loaded 53,940 diamond records | Know your inventory |
2. EDA | Data Analysis | Found carat drives 92% of price variance | Understand your market |
3. Feature Engineering | Data Engineering | Encoded cut/color/clarity, removed redundancy | Speak the model’s language |
4. Build & Train | Machine Learning | Trained Linear Regression + Random Forest | Build the pricing brain |
5. Evaluate | Machine Learning | MAE ~$540, R2 ~0.97 | Quantify trustworthiness |
6. Fine Tuning | Machine Learning | GridSearchCV, cross-validation | Push to production-ready |