Mental Health Fitness-Tracker

The Mental Health Fitness Tracker project focuses on analyzing and predicting mental fitness levels of individuals from various countries with different mental disorders. It utilizes regression techniques to provide insights into mental health and make predictions based on the available data. The project also provides a platform for users to track their mental health and fitness levels. The project is built using Python.

Table of Contents

• Mental Health Fitness-Tracker
  • Table of Contents
  • Installation
  • Usage
  • Contributing
  • License

Installation

To use the code and run the examples, follow these steps:

1. Ensure that you have Python 3.x installed on your system.
2. Install the required libraries by running the following command:

pip install pandas numpy matplotlib seaborn scikit-learn plotly.express

3. Download the project files and navigate to the project directory.

Usage

1. Select the country and the mental disorder you want to analyze.
2. Select the year range you want to analyze.
3. Click on the "Analyze" button.
4. The app will display the results of the analysis.
5. Click on the "Predict" button to predict the mental fitness level of the selected country.
6. The app will display the predicted mental fitness level of the selected country.
7. Click on the "Track" button to track your mental fitness level.
8. The app will display the results of the tracking.

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the repo
2. Clone the project
3. Create your feature branch
4. Commit your changes
5. Push to the branch
6. Open a pull request

License

Distributed under the ICS License.

References

• Datasets that were useD in here were taken from KAGGLE
• This project was made during my internship period for Edunet Foundation in association with IBM SkillsBuild and AICTE