I'm a Computer Engineer who enjoys building things to solve every kind of problems.
Most of my work sits somewhere between software development, analysis, and machine learning.
Right now I'm spending most of my time on machine learning, and practical AI projects.
A machine learning project focused on a real education problem: identifying students at risk of dropping out and understanding why they are struggling.
I built a classification model to flag higher education students at risk of dropout and a regression model to estimate GPA for that group and highlight the factors most related to low performance. The project uses data from 4,424 students and includes the full process from cleaning and EDA to model comparison and interpretation.
An exploratory data analysis project looking at what drives coupon acceptance. The goal was to move past charts and find patterns that could actually help explain customer behavior.
- Machine learning projects with a clear real-world use
- Feature engineering, and model evaluation
- Spring-based development
- Mobile application using native language or React-Native
- Projects where the technical work has to make sense to non-technical people too
| Area | Tools |
|---|---|
| Languages | Python, JavaScript, SQL, Java |
| Data work | pandas, NumPy, scikit-learn |
| Visualization | Matplotlib, Seaborn, Plotly |
| Development | React, React Native, Spring Boot, Node.js |
| Workflow | Jupyter, Git, Conda |