İlknur Yılmaz
deliprofesor
Data Scientist | Electronics & Communication Engineer | AR/VR & AI Enthusiast
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Comprehensive analysis of teaching-learning gamification strategies using quantitative and qualitative data. (DOI: 10.17632/yc4np572zs.1)
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This project analyzes a salary dataset to explore factors like experience, company size, remote work ratio, and country. It includes data cleaning, group analysis, visualizations, and machine learning models (linear regression and Random Forest) to predict salaries and identify key features.
Implements the Modified Omori Law (λ(t)=K(t+c)^-p) to model the decay of aftershock activity following the 2016 Central Italy main shock. Calculates key seismological parameters (p, c, K) using non-linear least squares (scipy.optimize.curve_fit) and provides an R² assessment (R²=0.9531) of the model fit. The analysis focuses on M ≥ 2.0 events.
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