My CardioPredict project combines a binary classification model with an interactive Streamlit dashboard for assessing cardiovascular disease risk. I built a leakage-free preprocessing pipeline with Scikit-Learn and deployed the app with Streamlit Cloud.
For my telecom churn project, I developed a classification pipeline and compared four machine learning models to identify high-risk accounts and churn drivers. I also built a regression pipeline to forecast California district median housing values.
As a Campus Ambassador at GeeksforGeeks, I organize coding events and workshops and promote technical learning across campus. My training in Machine Learning with AI from Internshala & IITM Pravartak earned me Top Performer, Grade A.
