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- 🎓 Final Year BE Student
- 🤖 Building Explainable AI systems (CNN + Grad-CAM)
- 🌐 Developing Full-Stack Applications (React + Node.js)
- 🔍 Focused on real-world implementation, not just theory
- Built CNN model for MRI classification (Glioma, Pituitary, Meningioma, No Tumor)
- Integrated Grad-CAM for visual explanation
- Focused on trust in AI predictions
- Designed preprocessing + training pipeline
🔗 GitHub Repo: https://github.com/TanmayT134/Explainable-Brain-Tumor-Detection
Below are actual outputs from the trained model demonstrating preprocessing and Grad-CAM explainability.
Preprocessing pipeline
💡 Tip: Click on any card to explore the project
- 🧠 Explainable AI (Grad-CAM improvements)
- 🌐 Full-stack project: EZStay
- ⚡ Optimizing CNN performance & deployment thinking
📌 I write about:
- Deep Learning (simple explanations)
- Project breakdowns
- Beginner-friendly guides
- 💼 ML / AI / Full-Stack Internships
- 🤝 Collaboration on impactful projects
- 🚀 Real-world problem solving
I don’t just build models — I focus on making them understandable, reliable, and usable in real-world scenarios.