I am a final-year B.Tech Computer Science & Engineering student at Royal Global University, specializing in Artificial Intelligence, Machine Learning, and Computer Vision. I am passionate about transforming raw data into actionable insights and building scalable AI models that solve real-world problems.
- 🔭 Current Focus: Advanced Deep Learning architectures, Computer Vision pipelines, and Edge AI.
- 💼 Experience: Developed a production-grade Convolutional Neural Network (CNN) during my internship at NIELIT that detects brain tumors in MRI scans with 96-98% accuracy.
- 🌱 Learning: Continuously exploring MLOps, Model Optimization for Edge Devices (Raspberry Pi), and Natural Language Processing.
| Project | Description | Tech Stack |
|---|---|---|
| Automatic Number Plate Detection | An edge-optimized ANPR system designed for Raspberry Pi. Features real-time traffic monitoring and logging via a custom web dashboard. | Python, YOLOv8, OpenCV, MobileNet |
| WhatsApp Chat Analyser | Analyzed 100,000+ messages using NLP. Built interactive visualizations showing sentiment analysis and emoji usage patterns. | Python, NLP, Streamlit, Pandas |
| Movie Recommendation Engine | Content-based recommendation system using cosine similarity across 50,000+ movies. Integrated with TMDb API. | Machine Learning, Scikit-Learn, API |
| TensorFlow Image Classification | Trained custom CNN models for multi-class visual recognition and deployed them via Streamlit for interactive use. | TensorFlow, Keras, OpenCV |
(Explore my full interactive portfolio here: strange0000.github.io/portfolio)
"I believe in learning by building. From recommendation engines to real-time number plate detection, I transform ideas into working AI-powered applications."