MMehmet Ünlü
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Mehmet Ünlü

I study Electronics and Communication Engineering at ITU and build hands-on projects around forecasting, computer vision, and making data workflows faster.

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Notes

Small writeups from the workbench.

Short writing around validation choices, metrics, optimization, visual odometry, and speech-processing workflows.

WhisperNLPDeployment

Building Self-Hosted Whisper Pipelines

Whisper becomes more useful when transcription is treated as one stage in a larger NLP system.

Computer VisionVisual Odometry

Hybrid Visual Odometry: RAFT + ORB

A confidence selector can turn deep and classical visual odometry branches into a more robust research architecture.

OptimizationNumPyPandas

Vectorization vs Python Loops in ML Pipelines

The fastest pipeline improvement is often moving repeated Python-level work into vectorized array operations.

Intermittent DemandLightGBM

Two-Stage Modeling for Intermittent Demand

Separating sale occurrence from sale magnitude can make sparse forecasting systems easier to reason about.

MetricsForecasting

Why WAPE Alone Can Be Misleading

WAPE is useful, but sparse demand and high zero ratios can hide important failure modes.

ForecastingValidationML Systems

Avoiding Data Leakage in Recursive Forecasting

A practical note on preserving temporal integrity when lagged features depend on previous predictions.