United States
Researcher with 7+ years of hands-on experience in collecting and analyzing data and reporting research results. Proficient in predictive modeling, data processing, Machine Learning algorithms, and Deep Learning. Certified AWS Machine Learning Specialty. Skills: Languages: Python (Pandas, Numpy, Scikit-learn, TensorFlow ) Machine Learning: Linear Regression, Logistic Regression, Decision trees, KNN, Clustering (K-means and Hierarchical), Principal Component Analysis, Cross-validation, Regularization, Pipelines, Up and Down Sampling, Bagging Classifiers (Bagging and Random Forest), Boosting Classifier (AdaBoost, Gradient Boosting, XGBoost, Stacking Classifier), Hyperparameter Tuning using GridSearchCV and RandomizedSearchCV Deep Learning: ANN, CNN Data Visualization: Matplotlib, Seaborn Cloud Services: AWS SageMaker, S3, EC2, Glue https://github.com/fkayakent https://eportfolio.mygreatlearning.com/fatma-kaya
Creating pipelines, data ingestion, ETL processes, data storing, AWS, machine learning, object detection, and sentiment analysis
- Collecting and analyzing quantitative and qualitative data; Using parametric and non-parametric tests to analyze data; Reporting and communicating findings and writing manuscripts; Linear Regression;
- Data collection via Qualtrics; Survey development via the Rasch model; Mixed methods research design; Text mining via NVivo and Dedoose; Quantitative methods applying regression models; Presenting at conferences