Welcome to my data science portfolio! This repository showcases my expertise in machine learning, data analysis, and business intelligence across diverse domains. Each project demonstrates end-to-end analytical workflows from data cleaning to actionable insights.
Machine Learning | Regression Analysis | Automotive Industry
Developed a predictive model to estimate used car prices for Eureka Motors, enabling data-driven pricing strategies.
Key Highlights:
- Built machine learning models for price prediction
- Analyzed automotive market data patterns
- Delivered actionable insights for pricing optimization
Technologies: Python, Jupyter Notebook, Machine Learning Algorithms
HR Analytics | Predictive Modeling | Business Intelligence
Comprehensive 4-stage analysis of employee attrition patterns and performance metrics for strategic HR decision-making.
Key Highlights:
- Stage 1: Project planning and requirements analysis
- Stage 2: Advanced data cleaning and preprocessing (1,470 employees, 35+ features)
- Stage 3: Feature engineering and model preparation
- Stage 4: Predictive modeling and business insights
Impact: Identified key attrition drivers and provided recommendations for employee retention strategies.
Technologies: Python, pandas, scikit-learn, Statistical Analysis
Public Safety Analytics | Data Visualization | Statistical Analysis
Dual-approach analysis of Queensland road safety data combining statistical modeling and interactive visualization.
Key Highlights:
- Insight 1: Statistical analysis using R for pattern identification
- Insight 2: Interactive dashboard development with Tableau
- Identified critical safety factors and accident patterns
Technologies: R, Tableau, Statistical Modeling, Data Visualization
| Category | Technologies |
|---|---|
| Programming | Python, R |
| Data Analysis | pandas, numpy, statistical analysis |
| Machine Learning | scikit-learn, predictive modeling, regression |
| Visualization | Tableau, interactive dashboards |
| Tools | Jupyter Notebooks, Git, VS Code |
Each project follows a structured approach:
- Problem Definition - Clear business objectives
- Data Collection & Exploration - Comprehensive data understanding
- Data Cleaning & Preprocessing - Ensuring data quality
- Analysis & Modeling - Applying appropriate techniques
- Insights & Recommendations - Actionable business outcomes
These projects demonstrate my ability to:
- Transform raw data into strategic business insights
- Build predictive models for real-world applications
- Communicate complex findings to stakeholders
- Work across multiple industries (automotive, HR, public safety)
Ready to discuss how data science can drive your business forward? Let's connect!
*This portfolio represents individual and collaborative