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https://github.com/ikanurfitriani/diabetes-prediction

This repository contains code archives for Diabetes Prediction with Machine Learning
https://github.com/ikanurfitriani/diabetes-prediction

decision-tree diabetes-dateset-analysis diabetes-prediction diabetes-prediction-model ipynb-jupyter-notebook jupyter-notebook knn-algorithm linear-regression logistic-regression-algorithm naive-bayes-algorithm python random-forest streamlit-webapp svm-model

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This repository contains code archives for Diabetes Prediction with Machine Learning

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# Diabetes Prediction
This repository contains a Streamlit application for predicting diabetes based on user input parameters. The prediction is made using a pre-trained machine learning model.

## Deployment
Link deployment for public:
https://diabetes-prediction-by-ika.streamlit.app/

## Contents
- `app.py`: The main Streamlit application script.
- `diabetes_model.pkl`: The trained machine learning model used for prediction.
- `scaler.pkl`: The scaler used to normalize the input features.
- `Diabetes_Prediction-Ika_Nurfitriani.ipynb`: A Jupyter Notebook used for model training and evaluation.
- `requirements.txt`: To specify the Python packages and their versions that are required to run diabetes prediction application.

## Usage
1. User Input: Enter the required parameters for the prediction.
- Pregnancies
- Glucose
- Blood Pressure
- Skin Thickness
- Insulin
- BMI
- Diabetes Pedigree Function
- Age
2. Prediction: Click the `Predict` button to get the prediction.
- The application will display whether the person is diabetic or non-diabetic.
- If available, the prediction probabilities will also be displayed.

## Project Setup / Installation Instructions
1. Clone the repository from GitHub:
```
git clone https://github.com/ikanurfitriani/Diabetes-Prediction.git
```

2. Navigate to the project directory:
```
cd Diabetes-Prediction
```

3. Install the required dependencies:
```
pip install -r requirements.txt
```

4. Run the Streamlit application:
```
streamlit run app.py
```

## Screen Capture
The following is a screen capture from the Diabetes Prediction App:
- `SS1`
SS1

- `SS2`
SS1

## Author
[@Ika Nurfitriani](https://github.com/ikanurfitriani)