Building practical AI applications while strengthening the fundamentals.
I'm Suhaib Iqbal, a CSE student specializing in AI & ML. My projects explore AI-assisted learning, computer vision, and web applications. I also practice Python problem solving and document my coursework here.
I care about understanding how a system works, writing clearer code, and turning experiments into useful applications.
| Project | What it explores | Core technologies |
|---|---|---|
| AI Tutor Platform | Tutoring, coding practice, quizzes, study planning, and document-based learning | TypeScript, Next.js, Express, Prisma, PostgreSQL |
| Vision Reality | Webcam effects, hand gestures, YOLO detection, and marker-based AR | Python, OpenCV, MediaPipe, PyTorch |
| TomatoGuard | Image upload, prediction history, and an optional leaf-classification model workflow | Node.js, Express, MongoDB, EJS |
These are development and educational projects. Each README explains setup, current behavior, and limitations. TomatoGuard includes simulation mode; trained model weights are not bundled.
| Area | Tools |
|---|---|
| Programming | Python, TypeScript, JavaScript |
| Web applications | Next.js, React, Express, FastAPI |
| AI and vision | Gemini integrations, OpenCV, MediaPipe, YOLO |
| Data | PostgreSQL, Prisma, MongoDB |
| Development | Git, GitHub, VS Code, Jupyter |
- Python problem solving — LeetCode solutions and a topic index.
- AI & ML labs — Notebooks, search algorithms, and coursework reports.
- Generative AI · 2025 — Weekly notebook exercises.
- AI-assisted coding — PDF lab submissions.
- DevOps · 2026 — Dated lab archives.
- Building and refining AI learning applications.
- Exploring webcam computer vision and interactive AR.
- Improving Python, data structures, and algorithmic reasoning.
- Making project documentation easier to follow and reproduce.
Browse the pinned repositories below for a starting point. For questions about a public project, open an issue in its repository.