Tech Enthusiast | Undergraduate Student | C/C++, JavaScript | Game development , Web , Machine Learning

codeforces

github

Kunal Sonne  • Peerlist

•Developed and deployed a scalable Heart Health Monitoring web application using Flask for backend development and HTML/CSS for responsive frontend design.

•Implemented hybrid machine learning model using a Stacking ensemble technique, achieving an accuracy of over 90% in predicting the likelihood of heart disease based on a public health dataset of over 1000 records.

•Optimized model performance by integrating multiple algorithms, resulting in a 15% improvement in prediction accuracy. Integrated a user-friendly dashboard to visualize health metrics and trends, improving patient insights
into their heart health status.

Machine learning based Heart Disease Detection

•Leveraged Computer vision to enable reduction in response time for event management teams by optimizing resource distribution during high-traffic events.

•Integrated OpenCV for real-time video processing, enabling accurate detection of crowd sizes and dynamic updates to maps with live crowd information.

•Developed and trained a machine learning model on a dynamic dataset of previous data entries to predict future crowd densities and trends effectively.

•Collaborated with a cross-functional team to enhance UI/UX design, ensuring seamless integration between the frontend and backend for a user-friendly experience.