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Profil
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Erfahrungen
Applied ML algorithms (Linear/Logistic Regression, Naive Bayes) on real-world datasets. Performed data pre-processing, EDA, and clustering-based customer segmentation. Used Python (Pandas, NumPy, Scikit-learn) and SQL for analysis and visualization.
Gained hands-on experience in data analysis through training and practical projects. Focused on skill development and implementation in real-world scenarios.
Built a logistic regression model to predict heart disease with 88.5% accuracy, 87.9% recall, and 92.0% ROC AUC. Performed data cleaning, EDA, feature selection (p < 0.05), and evaluated performance using classification metrics and ROC curve.
