Dr Dilek Celik
Sr Data Scientist
SKILLS
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
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
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.