The Mental Fitness Tracker is a web application of AI development as part of my IBM Artificial Intelligence internship project. The primary objective of this project is to help users monitor and improve their mental well-being.
You can also explore Mental Fitness Tracker via video Mental-Fitness-Tracker
Table of Contents
Introduction
Features
Getting Started
Usage
Technologies Used
Machine Learning Model
Contributing
Support
License
Introduction
In our busy daily lives, it's essential to take care of our mental health. The Mental Fitness Tracker provides a user-friendly platform where individuals can track various aspects of their mental fitness and gain insights into their well-being. The application uses machine learning regression models to predict the user's mental fitness score based on a combination of numerical data and textual information provided by the user. The predicted score can offer valuable insights into one's mental well-being and serve as a guide to making positive changes in daily life.
Mental Fitness Tracker: INPUT
Input of model
Mental Fitness Tracker - OUTPUT output of model
Please note that the Mental Fitness Tracker is not a substitute for professional mental health advice. If you or someone you know is struggling with mental health issues, please seek support from a qualified mental health professional.
Features User-friendly interface for entering mental fitness data
A machine learning regression model for predicting mental fitness score
Insightful feedback and guidance based on predicted score
About and Contact pages for additional information and support
Getting Started To run the Mental Fitness Tracker locally, follow these steps:
Clone the repository: git clone https://github.com/Abhishek676062/Mental-Fitness-Tracker
Navigate to the project directory: cd Mental-Fitness-Tracker
Open index.html in your web browser to access the application. Usage
Open index.html in your web browser.
Enter the required data in the input fields provided on the page. Click the "Predict" button to view your estimated mental fitness score.
For more information, check the "About" and "Contact" pages. Technologies Used
The Mental Fitness Tracker project utilizes the following technologies:
HTML CSS (including inline CSS for styling)
JavaScript (including inline JavaScript for basic interactivity)
Flask (for back-end server and handling requests)
Machine learning libraries (for the regression model)
Machine Learning Model The Mental Fitness Tracker employs a machine learning regression model to predict the mental fitness score. The model is trained on a dataset of mental fitness data and uses a combination of numerical features and textual input to make predictions. The model's accuracy and performance have been evaluated to ensure reliable results.
Contributing Contributions to the Mental Fitness Tracker project are welcome! If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request. We appreciate your feedback and support in making this project better.
Support If you have any questions or need assistance with the Mental Fitness Tracker, you can reach out to us using the contact information provided in the "Contact" page of the application. We value your input and will do our best to respond to your inquiries in a timely manner.