Dental caries analysis. For analysis i used: k-means clustering, k-neighbors classifier, decision tree classifier. Libraries: scikit-learn.

Coronary heart disease analysis, dataset - https://www.kaggle.com/datasets/billbasener/coronary-heart-disease. For analysis i used: k-means clustering, k-neighbors classifier, decision tree classifier. Libraries: scikit-learn.

This project analyzes the chemical properties of wines to identify key factors influencing quality. By leveraging machine learning techniques, i aim to develop predictive models that accurately classify wine quality, providing valuable insights for producers and enthusiasts alike.

Using supervised Machine Learning algorithms to build models for classification of Heart Diseases among patients and predicting the risk of getting a Heart Disease in the future.

This project focuses on building a fraud detection model for credit card transactions using a dataset containing transactions made by European cardholders in September 2013. We are working with a highly unbalanced dataset and the challenge lies in effectively detecting fraudulent transactions while minimizing false positives.

Stroke analysis, dataset - https://www.kaggle.com/datasets/fedesoriano/stroke-prediction-dataset. For analysis i used: mlp classifier, k-means clustering, k-neighbors classifier. Libraries: tensorflow, scikit-learn.

ML model to predict cardiovascular disease

Credit scoring is a crucial task in financial institutions to assess the creditworthiness of individuals or businesses. This project focuses on building classification models to predict credit scores based on various features such as income, debt, and credit history.

Heart-Disease Prediction

The datasets contains transactions made by credit cards in September 2013 by european cardholders. This dataset presents transactions that occurred in two days, where we have 492 frauds out of 284,807 transactions.

Developed a text classification model to classify SMS as spam or nonspam using Python.

Experimenting ML Algorithms, feature selection, cross validation and feature transformation on self-annotated custom Eskişehir real estate dataset. - 2021 - Yildiz Technical University