I craft intelligent solutions with code and creativity
🧠I don't just analyze data; I synthesize strategic wisdom
🧬 I don't just write code; I architect scalable systems
🔮 I don't just adapt to now; I pioneer the digital future
Get to know me better
I'm a dedicated Data Science student at JG University with a strong academic foundation (CGPA: 8.75). My journey combines analytical thinking with creative problem-solving, allowing me to build meaningful full-stack applications and develop intelligent AI/ML models that make a real impact.
What drives me is the excitement of discovering patterns in data and transforming them into solutions that matter. I love working with modern web technologies, exploring machine learning algorithms, and creating applications that bridge the gap between complex data and user-friendly experiences.
Technologies I work with
Python, JavaScript, Java, C++, C, SQL, PHP
Scikit-learn, XGBoost, Random Forest, Predictive Analytics, Data Mining
React.js, HTML5, CSS3, Responsive Design, WebSocket, Streamlit
SQL (Intermediate), Database Design and Management, Data Structures
Git, Jupyter Notebook, VS Code, Cursor, AI Tools Integration
MS Office Suite, Public Speaking, Leadership, Problem Solving, Team Collaboration
Academic excellence and certifications
July 2024 - April 2027
CGPA: 8.75/10.0
June 2022 - May 2024
Grade : A2
Successfully completed high school education
June 2022
Grade : B1
Successfully completed secondary school education
freeCodeCamp Certification
2025Outstanding Performance in Data Science
Semester 1 & 2LJ University - ThunderCast Project
September 2025Some of my recent work
A full-stack real-time chat application with instant messaging, WebSocket protocol, and responsive design across devices. Features user authentication and message persistence.
AI-powered weather prediction model for thunderstorms and gale force wind speeds. Developed at LJ University AI Hackathon with machine learning algorithms for meteorological data analysis.
Machine learning system for sales and profit prediction using multiple ML models (Linear Regression, Ridge, Random Forest, XGBoost) achieving R² > 0.85 accuracy.
Let's work together
I'm always interested in new opportunities and exciting projects. Whether you have a question or just want to say hi, I'll try my best to get back to you!