Projects For more details click the image.
Project 01: Asthma Risk Factors
Analyzed health data to identify key asthma predictors, built a Random Forest model for prediction, and visualized insights using Python, MySQL, and Tableau. Key insights: Smoking, Age, and Sleep Quality are major asthma predictors. Learned data cleaning, EDA, feature importance, and predictive modeling techniques. This helped predict asthma contributors with an accuracy of %97.
Project 02: Superstore Sales and Customer Behavior
I analyzed sales data from a retail company to understand customer behavior and sales performance. Using Python, MySQL, and Tableau, I performed data preprocessing to find the best selling products, customer segmentation, and created an interactive dashboard. I learned effective data visualization and the practical application of machine learning algorithms for market basket analysis.
Project 03: Sankey Diagram of Patient Condition Journeys
This diagram illustrates the flow and transition between different health conditions over time, based on data collected from the Harvard dataverse. Each colored link represents a transition from one condition to another, with the thickness of each link proportional to the number of patients making that transition. This visualization helps us quickly identify common pathways in patient treatment and condition progression, providing insights that can guide our future healthcare strategies and interventions.
Project 04: Bird Identifier App
I developed a MATLAB GUI application to accurately classify bird species using a convolutional neural network. I learned how to integrate pre-trained deep learning models for image classification and improve model accuracy through transfer learning. After training I was able to obtain recognition accuracy of %90.
