https://github.com/rohitinu6/diabetes-prediction
This project aims to predict the likelihood of a patient having diabetes based on health parameters.
https://github.com/rohitinu6/diabetes-prediction
data-science diabetes-prediction eda health-analytics healthcare-application jupyter-notebook machine-learning machine-learning-algorithms python visualization
Last synced: 3 months ago
JSON representation
This project aims to predict the likelihood of a patient having diabetes based on health parameters.
- Host: GitHub
- URL: https://github.com/rohitinu6/diabetes-prediction
- Owner: rohitinu6
- Created: 2025-01-29T10:50:47.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-06T03:01:46.000Z (over 1 year ago)
- Last Synced: 2025-02-22T17:37:54.554Z (over 1 year ago)
- Topics: data-science, diabetes-prediction, eda, health-analytics, healthcare-application, jupyter-notebook, machine-learning, machine-learning-algorithms, python, visualization
- Language: Jupyter Notebook
- Homepage:
- Size: 1.18 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Diabetes Prediction
## 📌 Project Overview
This project aims to predict the likelihood of a patient having diabetes based on health parameters. By utilizing machine learning models, it provides insights into potential diabetes risks and assists in early diagnosis.
## 🚀 Features
- Data preprocessing and exploratory data analysis (EDA)
- Feature selection and engineering
- Machine learning model development
- Model evaluation and optimization
## 🛠 Tech Stack
- Python
- Pandas, NumPy
- Scikit-learn
- Matplotlib, Seaborn
- Jupyter Notebook
## 📂 Dataset
The dataset includes various medical parameters such as:
- **Age**
- **Blood Pressure**
- **Glucose Levels**
- **BMI**
- **Insulin Levels**
- **Diabetes Pedigree Function**
## 📊 Machine Learning Models Used
- Logistic Regression
- Random Forest Classifier
- Support Vector Machine (SVM)
- XGBoost
## 🔥 Results
The models are evaluated based on accuracy, precision, recall, and AUC-ROC score. The best-performing model provides reliable predictions for diabetes risk.
## 📁 Repository Structure
```
📂 Diabetes-Prediction
👉 📂 data (Dataset & processed data)
👉 📂 notebooks (Jupyter Notebooks)
👉 📂 models (Trained models)
👉 📂 images (Code and Results Screenshots)
👉 📄 README.md (Project documentation)
```
## 🖼 Code and Results
Include images of code and results in the `images` folder. Example:
## 💜 How to Run the Project
1. Clone the repository:
```bash
git clone https://github.com/rohitinu6/Diabetes-Prediction.git
```
2. Navigate to the project folder:
```bash
cd Diabetes-Prediction
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Run the Jupyter Notebook or Python scripts to train and test models.
## 📞 Links
- **GitHub Repository:** [Diabetes Prediction](https://github.com/rohitinu6/Diabetes-Prediction.git)
- **Portfolio:** [Rohit Dubey](https://tinyurl.com/dubeyrohit)
- **GitHub Profile:** [rohitinu6](https://github.com/rohitinu6)
- **LinkedIn:** [Rohit Dubey](https://www.linkedin.com/in/rohit-dubey-d/)
- **Twitter/X:** [@rohitdubey003](https://x.com/rohitdubey003)
## 🗝 Tags
`Machine Learning` `Diabetes Prediction` `Health Analytics` `Data Science` `Python` `EDA`
## 📝 License
This project is licensed under the [MIT License](https://opensource.org/licenses/MIT).
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💡 **For any queries or collaboration opportunities, feel free to connect!** 🚀