I'm a Data Science and Economics and Statistics graduate focused on turning data into actionable insights using Python, SQL, and machine learning.
- Analyze and clean real-world datasets
- Build machine learning models for prediction and segmentation
- Create data visualizations and dashboards
- Extract insights to support decision-making
- Languages: Python, SQL
- Libraries: Pandas, NumPy, Scikit-learn
- Visualization: Matplotlib, Seaborn, Power BI
- Databases: MySQL / PostgreSQL
- Tools: Git, Jupyter Notebook, Excel
- Customer Segmentation using K-Means Clustering
- Loan Default Prediction Model
- Improving machine learning model performance
- Building more real-world data projects
- Enhancing project documentation and presentation
- LinkedIn: www.linkedin.com/in/emily-david-ds
- Email: emilyndanu2019@gmail.com