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Dr Dilek Celik
Sr Data Scientist


Python | SQL | Keras | Tensorflow | SciKit-Learn | Pandas | NumPy | SciPy | Matplotlib | Seaborn | ggplot2 | Jupyter Notebook | R Markdown | Advanced Statistics (SPSS, A/B Testing) | Hadoop | Cloud (AWS, Azure) | Tableau

Data Science & Machine Learning Projects

Fraud Detection

  • Build and maintain Logistic Regression, Random Forest, Deep Neural Network models

  • Performed Exploratory Data Analysis (EDA), Statistical Data Analysis, Data Cleaning, Handle Missing Data, Outliers Check, Feature Engineering, Data Pre-processing (Train-test split, Scaling, SMOTE), Built Models, Cross-Validation, Evaluation with confusion_matrix and classification_report, Compare Models, Predictions, Model Deployment 

  • Deployed Logistic Regression Model with 95% accuracy score using Flask on AWS cloud

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Regression Project - Car Price Prediction

  • Build Linear Regression, Ridge Regression, Lasso Regression, Elastic-Net algorithms

  • Performed end to end Data Science steps, Exploratory Data Analysis, Quantitative Data Analysis, Data Cleaning, Feature Engineering, Multicollinearity Check, Detect Outliers, Pre-Processing, Implement Models, Cross-Validation, Feature Importance, Compare Models, Save Model, Predictions

  • Building model using pandas, numpy, matplotlib, seaborn, sklearn, scipy, cross_validate. 

  • Evaluated models using the following metrics mean_absolute_error, mean_squared_error, r2_score, root mean squared error

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Customer Segmentation Cluster Analysis with Un-supervised Learning

  • Built K Means Clustering, Hierarchical Clustering (AgglomerativeClustering) models

  • Performed Exploratory Data Analysis (EDA), Quantitative Data Analysis, Data Cleaning, Detect Missing Values and Outliers, Outliers removal with IQR and Zscore, Data Pre-Processing, Cluster Analysis, Built Models 

  • Used tools are pandas, numpy, sklearn, scipy, matplotlib, seaborn, yellowbrikcs. 

  • Performed Cluster Analysis with Hopkins, Elbow Method, Silhouette Score, Dendogram.

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