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both crazy and energetic
🤪
both crazy and energetic
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deliprofesor/README.md

Header

Python R Julia Jupyter SQL Pandas NumPy Matplotlib Seaborn Scikit-Learn TensorFlow Keras PyTorch Maya Blender C# Unity Canva

👩‍💻 İlknur Yılmaz | Data Analyst & AR/VR Enthusiast

Elektronik ve Haberleşme Mühendisliği son sınıf öğrencisiyim. Veri bilimi, artırılmış ve sanal gerçeklik (AR/VR) teknolojileriyle yeni nesil çözümler geliştirme tutkusuna sahibim.

"Data really powers everything that we do."

🌟 Uzmanlık Alanlarım

  • 📊 Veri Analizi ve Makine Öğrenimi: Python, Julia, R, TensorFlow, Scikit-learn.
  • 🌐 AR/VR Geliştirme: Unity, Blender, Maya ile gerçek zamanlı projeler.
  • 🔧 Devre ve Sistem Tasarımı: STM32, Altium Designer ile elektronik projeler.

🏆 Başarılarım

💡 Daha fazla bilgi için LinkedIn ve Kaggle profillerimi ziyaret edin!

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  1. Breast-Cancer-Detection-Using-SVM-with-SMOTE-and-Model-Optimization Breast-Cancer-Detection-Using-SVM-with-SMOTE-and-Model-Optimization Public

    This project analyzes health and lifestyle factors influencing heart attack risk using statistical methods and machine learning, with Ridge Regression identified as the best predictive model.

    Python

  2. Cardiac-Data-Analysis-Exploring-Cholesterol-and-Heart-Rate Cardiac-Data-Analysis-Exploring-Cholesterol-and-Heart-Rate Public

    This project analyzes a heart disease dataset to explore the relationship between cholesterol, heart rate, and chest pain type. It includes normality tests, outlier detection, correlation analysis,…

    Python

  3. Health-Status-and-Heart-Attack-Risk-EDA-Regression-and-Hypothesis-Testing-Analysis Health-Status-and-Heart-Attack-Risk-EDA-Regression-and-Hypothesis-Testing-Analysis Public

    This project analyzes health and lifestyle factors influencing heart attack risk using statistical methods and machine learning, with Ridge Regression identified as the best predictive model.

    Jupyter Notebook

  4. K-Means-Clustering-for-Retail-Data-Analysis K-Means-Clustering-for-Retail-Data-Analysis Public

    This project uses K-Means clustering to segment wholesale customers based on their spending habits. The data is preprocessed, scaled, and clustered into four groups. The Elbow and Silhouette metho…

    R

  5. Multivariate-Analysis-of-Heart-Disease-Data-using-MANOVA Multivariate-Analysis-of-Heart-Disease-Data-using-MANOVA Public

    This project applies MANOVA to heart disease data, examining the impact of chest pain type (cp), cholesterol (chol), and heart rate (thalach). It includes normality tests, outlier detection, post-…

    R

  6. Behavioral-Insights-and-Data-Exploration Behavioral-Insights-and-Data-Exploration Public

    This project analyzes Spanish speech data, focusing on acoustic features and demographics. It includes data cleaning, outlier detection, clustering, and time series modeling (ARIMA, Holt-Winters) t…

    Python