ML POWER
◆ PROJECT WORLD
SmartPAY
ML Salary Predictor
ML regression models trained on 3,000+ salary records. 85%+ prediction accuracy — cuts HR workload by 60%.
◆ WORLD
Fiery Gorge of Kilauea
Volcanic data forges where salary models are refined.
▶ TILESET
Dataset Core
3,000+ salary records
Cleaning Step
Null and noise handling
Feature Build
Role, exp, location
Model Bench
Regression comparisons
Eval Metrics
MAE / RMSE / R2
Inference API
Prediction service
Bias Check
Fairness sanity pass
Report Export
HR-ready summaries
▶ ASSETS
Prediction Form
Input salary factors
Result Panel
Estimated compensation
Model Insights
Feature impact view
Trend Charts
Market comparison
Batch Mode
Multiple candidate runs
HR Dashboard
Planning assistance
◆ MISSION BRIEF
PROBLEM
Salary estimation was manual, inconsistent, and time-consuming for HR teams.
SOLUTION
A data-driven salary prediction engine using cleaned historical records and ML regression.
OUTCOME
Reached 85%+ accuracy on 3,000+ records and significantly reduced manual HR effort.
▶ KEY HIGHLIGHTS
- Trained and compared multiple regression model variants
- Performed feature engineering and outlier handling on salary data
- Built prediction flow for quick HR planning and benchmarking
- Presented explainable insights for non-technical business users
▶ PROJECT STATS
85%+
ACCURACY
3,000+
RECORDS
-60% work
HRSAVED
▶ TECH STACK
PythonScikit-learnPandasNumPy
▶ VIEW CODE