I’m Derin, an AI / Machine Learning enthusiast fascinated by systems
that can observe, learn, and generalize from data.
My interests sit at the intersection of
Computer Vision, Applied ML, and research-driven experimentation.
Currently focused on building skills around
deployment-ready models, backend integration,
and clean, maintainable ML pipelines.
- Neural Representation Learning — studying how deep models encode and transform information
- Computer Vision — learning visual abstractions from images and spatial data
- Applied Machine Learning — evaluating models on real-world constraints and datasets
- ML Experimentation & Reproducibility — designing clean, repeatable training workflows
- Advanced PyTorch workflows
- ML model deployment with FastAPI
- Writing cleaner and more readable ML code
- Designing end-to-end ML systems
- Build and ship 3 meaningful AI projects
- Complete 150+ DSA problems
- Build stronger PyTorch fundamentals
- Deploy an ML model end-to-end
- Read and implement 10 research papers
- Contribute to an open-source project
- Build a consistent GitHub contribution habit
- Reach 100 WPM typing speed
- Learn something new every day
Getting 1% better — one commit at a time.