Diabetes Prediction Project

This project is a Python-based Machine Learning project using a diabetes dataset.

The project focuses on exploring, cleaning, and visualizing diabetes data, then using a Logistic Regression classification model to predict the diabetes outcome based on different health-related factors.

Project Workflow

• Data Exploration
• Data Cleaning
• Data Visualization
• Logistic Regression Classification
• Model Evaluation

Technologies Used

• Python
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Scikit-learn

Machine Learning Model

Logistic Regression is used as a supervised machine learning classification model to predict whether the diabetes outcome is negative or positive based on the available health-related features.

Dataset

The dataset contains health-related information such as:

• Glucose level
• Blood pressure
• Skin thickness
• Insulin
• BMI
• Age
• Other health-related factors

Team Members

1. Malak Atallh Hussein
2. Rania Mohamed Hamad
3. Nadine Wael Hamdy
4. Habiba Mohamed Sayed
5. Ashrakat Sabra Mohamed

• README.md — Project documentation