Diabetes Prediction Decision Tree

This project’s goal was to use Python and the pandas library to analyze a CSV dataset and to build a decision tree model for predicting a patient’s likelihood of having diabetes based on various inputs. I explored the data and applied a decision tree model to identify patterns within the data. The results showed that the model could make predictions based on the data, such as number of pregnancies, glucose levels, insulin levels, BMI, age, etc. Through this project, I have learned how to process real-world data, apply decision tree models, and interpret outputs.