ML Based Heart Stroke Prediction
A machine learning pipeline that predicts the likelihood of a patient experiencing a heart stroke using structured health report data.
Self-taught Machine Learning & IoT enthusiast, currently pursuing AI & ML at Madanapalle Institute of Technology and Science. I enjoy turning ideas into end-to-end projects spanning ML, automation and web.
A quick overview of who you are, what you are learning, and what kinds of problems you enjoy solving.
I am an AI & ML student with a strong interest in building practical solutions using machine learning, deep learning, IoT, and automation. I enjoy exploring new tools, experimenting with models, and deploying projects that can help people in healthcare, security, and everyday automation.
Most of my work combines Python-based ML stacks with simple web frontends and embedded systems, allowing me to go from data and sensors all the way to interactive applications and dashboards.
Technologies and tools used across machine learning, web, and embedded systems.
Selected work across machine learning, health monitoring, and security systems.
A machine learning pipeline that predicts the likelihood of a patient experiencing a heart stroke using structured health report data.
Early disease detection system targeting stenosis-related heart disease and mouth cancer, designed to assist cardiologists and ENT doctors.
A hardware-based security alert system designed for theft protection, integrating sensors and alarms for real-time notification.
Academic background and practical work that shaped your current skill set.
Studying core concepts of artificial intelligence and machine learning while applying them to hands-on projects in healthcare, automation, and security.
Developed a strong foundation in core engineering concepts and problem solving, which helped in transitioning into AI and ML domains.
Actively contributing projects to GitHub, focusing on practical ML pipelines, web integrations, and automation scripts.
Highlights that reflect your initiative and performance in competitive settings.
Secured 14th place as an individual participant in an AI/ML hackathon, showcasing strong problem-solving, implementation, and self-learning abilities under time constraints.
Qualified the GATE 2026 examination, demonstrating strong fundamentals in engineering and problem solving.
Open to internships, collaborations, and interesting project ideas in AI, ML, IoT, and automation.
If you’d like to discuss a project, potential collaboration, or internship opportunity, feel free to reach out. The easiest way to contact me is via email or LinkedIn.