Diabetes Detection System using Machine Learning Overview This project presents a Machine Learning-based Diabetes Detection System that predicts whether a person is likely to have diabetes based on medical attributes. The system analyses health indicators such as glucose level, BMI, blood pressure, insulin level, and other medical parameters to determine the probability of diabetes. The application demonstrates how machine learning techniques can be applied in healthcare to assist in early diagnosis and decision support.

Features Machine Learning model for diabetes prediction Real-time prediction results Data preprocessing and feature analysis Integration of backend ML model with web application

Technologies Used Programming Languages Python Libraries & Frameworks Scikit-learn Pandas NumPy Flask

Machine Learning Workflow Data Collection Data Preprocessing Feature Selection Model Training Model Evaluation Prediction System Deployment

The model is trained using a diabetes dataset containing medical diagnostic measurements, including: Pregnancies Glucose Level Blood Pressure Skin Thickness Insulin BMI Diabetes Pedigree Function Age

Installation Clone the Repository: git clone https://github.com/venkatraju3198/ML-Diabetes-Project.git Navigate to Project Directory: cd ML-Diabetes-Project Install Dependencies: pip install -r requirements.txt Run the Application: python app.py