I am Francis Boateng, and I work with data to transform complex information into meaningful insights. With a strong statistics, machine learning, and programming foundation, I leverage tools like Python, SQL, R, and Tableau to clean, visualize, and model data across various domains, including business, healthcare, finance, and higher education. Driven by curiosity and continuous learning, I expand my expertise through formal education and independent exploration. I thrive in independent and collaborative settings, bringing strong analytical, communication, and problem-solving skills to every challenge.
In this project, I developed and evaluated machine learning models for credit card fraud detection, achieving high accuracy rates. Demonstrated expertise in fraud detection, predictive modeling, and security enhancement, minimizing potential losses and showcasing ability to protect financial assets.
Conducted in-depth exploratory data analysis on a stroke dataset and developed a predictive machine learning model with an impressive 87% accuracy rate using GLM. Created an interactive R-Shiny app that provides dataset statistics, custom visualizations, and stroke occurrence predictions
Uncovered key insights into diamond pricing by analyzing cut, carat, and price attributes using Python for regression and visualization. Discovered significant trends, revealing carat weight and cut as crucial factors influencing diamond prices, and achieved an impressive 85.65% predictability rate in forecasting diamond prices.
An R-Shiny-based data collection application used to gather participant data related to sleep quality assessment. This application facilitates capturing essential information such as participant IDs, demographic details, and baseline characteristics.
Feel free to reach out and let's connect! Your messages are always welcome, and I'm excited to engage in meaningful conversations with you.