This project aims to predict the likelihood of diabetes in individuals using machine learning techniques. It utilizes the K-Nearest Neighbors (KNN) algorithm to analyze biomedical data and make predictions based on various features such as pregnancies, glucose levels, blood pressure, BMI, etc.
- Data: Contains the dataset used for training and testing the model.
- DiabetesPrediction.ipynb: Jupyter Notebook containing the code for data preprocessing, model training, and evaluation.
- README.md: This file providing information about the project.
Ensure you have the following dependencies installed:
- Python 3.x
- Jupyter Notebook
- pandas
- scikit-learn
- matplotlib
- numpy
- Rhimini Aimane: LinkedIn Profile