🩺 Diabetes Prediction Using Machine Learning

📘 Overview

The Diabetes Prediction System is a machine learning project that predicts whether a person is likely to have diabetes based on their medical and lifestyle data.
It leverages supervised learning algorithms to analyze various health parameters such as glucose level, BMI, blood pressure, insulin level, and age.

By training on medical datasets (like the PIMA Indian Diabetes Dataset), this system can help in early detection of diabetes, enabling better medical decisions and preventive measures.

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🎯 Objectives

• To analyze health-related data and identify key factors influencing diabetes.
• To build an accurate machine learning model that can predict diabetes risk.
• To demonstrate the power of data science in healthcare prediction and diagnosis.

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🧠 Algorithms Used

• Logistic Regression
• Random Forest Classifier
• Support Vector Machine (SVM)
• K-Nearest Neighbors (KNN)
• XGBoost (optional for advanced tuning)

The model with the best accuracy and ROC-AUC score is selected for deployment.

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🧩 Dataset

The project typically uses the PIMA Indian Diabetes Dataset, available from Kaggle or UCI Machine Learning Repository.

Dataset features include:

• Pregnancies
• Glucose
• Blood Pressure
• Skin Thickness
• Insulin
• BMI
• Diabetes Pedigree Function
• Age
• Outcome (1 = Diabetic, 0 = Non-Diabetic)

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⚙️ Workflow

1. Data Collection – Load and inspect the dataset.
2. Data Preprocessing – Handle missing values, normalize data, and split into train/test sets.
3. Model Training – Train multiple ML algorithms for comparison.
4. Evaluation – Compare models using accuracy, precision, recall, and F1-score.
5. Prediction – Predict whether a person has diabetes based on input features.
6. Deployment (Optional) – Deploy using Flask/Streamlit for a web interface.

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📊 Performance Metrics

• Accuracy
• Precision
• Recall
• F1 Score
• ROC-AUC Curve

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💻 Technologies Used

• Programming Language: Python
• Libraries: NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn
• Optional Frameworks: Streamlit / Flask for Web UI
• Dataset Source: Kaggle - PIMA Indian Diabetes Dataset

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🚀 How to Run the Project

1. Clone this repository:

   git clone https://github.com/Abhay-art-git/diabetes-prediction-ml.git