

Computer Science student with practical experience in machine learning, regression models, and data preprocessing using Python and scikit-learn
TECHNICAL SKILLS Programming Languages: C, Python Database Querying: SQL Blockchain: Solidity
AI & Data Tools: scikit-learn, NumPy, Pandas, Matplotlib Backend Frameworks: FastAPI Databases: SQL
PROJECTS Multilinear Regression Model– Developed a Multilinear Regression model for predictive analysis using multiple independent variables– Performed data preprocessing including feature selection and normalization– Evaluated model performance using standard error metrics– Tools: Python, NumPy, Pandas, scikit-learn Cancer Prediction System (Breast, Colon, Prostate)– Designed and implemented a machine learning–based cancer prediction system for multiple cancer types– Trained and evaluated predictive models on structured medical datasets– Applied data preprocessing, feature engineering, and model evaluation techniques– Focused on early-stage risk prediction to support clinical decision-making– Tools: Python, scikit-learn, Pandas, NumPy
CERTIFICATIONS • Data Science: Machine Learning Specialist Career Path – Codecademy Credential ID: F51810B6-F