This repository showcases my journey in applying machine learning to solve problems in various domains, from business analytics to health sectors. Below are categorized projects demonstrating my expertise in building predictive models, performing segmentation, and deploying user-friendly applications.
- 🚗 Travel Insurance Claim Prediction - Binary Classification: Created a predictive model to identify customers likely to claim insurance from a dataset of 44,000 records.
- 🛒 Customer Segmentation of Online Retail: Utilized RFM quantile analysis and K-means clustering to segment over 500,000 transactions from a UK-based online retailer.
- 🏡 House Price Prediction in Bandung, Indonesia: Built a regression model based on the web-scraped data of 3,000 house prices in Bandung.
- 🩺 Early Risk Diabetes Prediction: Developed a model to predict prediabetes risks using research data.
- ❤️ Heart Disease Prediction: Created a classifier to assess heart disease risks based on medical records.
- 🧬 Acute Leukimia Prediction: Constructed a prediction model based on gene expression data (DNA microarray) to discriminate whether patient's acute leukimia case is considered as AML (Acute Myeloid Leukimia) or ALL (Acute Lymphoblastic Leukimia)
- 📱 Early Diabetes Predictor App: A Streamlit app providing users with instant diabetes risk feedback.
- 📱 Heart Disease Predictor App: Assists healthcare staff in assessing heart disease risk from medical records.
Feel free to explore the projects and Apps above. I’m always looking to collaborate on machine learning projects, so don’t hesitate to reach out if you’d like to work together!