Topwork – Freelance Handyman Marketplace Platform
Python, SQL
- Designed and developed a platform for freelance handyman workers to create profiles and be hired by local customers through a streamlined, user-friendly interface.
- Built backend services in Python and structured the database using SQL to handle user registration, job listings, and search queries.
- Created a recommendation feature to match customers with suitable workers, achieving over 80% accuracy in user-to-worker connections.
- Focused on accessibility and simplicity to ensure smooth adoption among non-technical users.
Smart Expense Categorizer – Automated Budget Classification Tool
Python, scikit-learn, regex
- Developed a machine learning model that automatically classifies user expenses into budget categories (e.g., “Starbucks” → Food & Drink) from CSV transaction data.
- Applied text preprocessing and regular expression-based keyword extraction to engineer features from vendor names and descriptions.
- Trained and evaluated multiple classifiers (Naive Bayes, decision trees), achieving over 80% accuracy on a labeled dataset of real-world transactions.
- Designed the system to support scalable input formats and provide quick insights into user spending habits for budgeting applications.