I'm Francis Boateng, a data enthusiast skilled in using analytics tools for scientific problem-solving in business, healthcare, and finance. I have a strong background in statistics, machine learning, and programming with proficiency in Python, SQL, and R. I use these skills to clean up data, make it visual, and create models. I continuously expand my knowledge through formal education and independent exploration to tackle new challenges effectively. I'm good at working independently or in a team, with strong interpersonal and communication skills. Please explore my portfolio, where I showcase my journey and expertise in data science, analytics, and its applications.
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.