AI Powered Mental Health Prediction System using Python Machine Learning (ML)

An AI-powered intelligence wellness prediction system Project is a package exertion that utilises instrumentality learning algorithms to analyse psychological and behavioural data. Based connected this analysis, the strategy predicts a user’s intelligence wellness status, facilitating early discovery and awareness.

AI-powered intelligence wellness prediction system is developed utilizing Python, 1 of the astir celebrated languages for AI and information science, and trained connected intelligence wellness study datasets to execute reliable prediction accuracy.

 🛠️ Tech Stack Used

 Frontend / Web Interface:

• Django (Python Web Framework) – Used to create the web interface for personification input, displaying predictions, and managing data
• HTML5, CSS3, JavaScript – For rendering and styling web pages
• Bootstrap (optional) – For responsive UI components
• Django Templates – For move web page rendering

 🧠Machine Learning / Backend Logic:

• scikit-learn – Machine Learning room utilized to instrumentality algorithms for illustration Logistic Regression, Decision Tree, Random Forest, KNN
• NumPy→ For numerical operations and matrix manipulation
• Pandas → For handling and preprocessing datasets
• joblib → To prevention and load the trained instrumentality learning model

 🗃️ Database:

• SQLite – Lightweight relational database utilized to shop personification information and predictions
• Django ORM (Object Relational Mapper) – Handles relationship betwixt Django models and the SQLite database

  ⚙️Tools & Environment:

• Python 3.x – Core programming connection used
• PyCharm – IDE for development
• Virtualenv / pip – For managing dependencies

✅ Key Features

• User Authentication System
  Secure signup, login, logout, and password guidance for some users and administrators.
• Mental Health Prediction
  Uses a instrumentality learning exemplary to foretell intelligence wellness consequence based connected personification inputs.
• Multiple Risk Categories
  Classifies users into Healthy, Low Risk, Moderate Risk, and High Risk categories.
• Risk Percentage Calculation
  Provides a normalised consequence percent for amended mentation of results.
• Personalized Suggestions
  Offers guidance and recommendations based connected predicted intelligence wellness status.
• Prediction History Tracking
  Allows users to position past prediction records for self-monitoring.
• User Profile Management
  Enables users to position and update their individual information.
• Admin Dashboard
  Displays full users, consequence distribution, and wide strategy statistics.
• User Management
  Admin tin view, search, filter, and negociate registered users.
• Secure and User-Friendly Interface
  Designed pinch a clean, intuitive layout for easy navigation and usability.

AI-Powered Mental Health Prediction successful Python & ML: Output Screenshot

Login Page

Signup/Registration

Dashboard

Prediction Form

Prediction Result

How to tally the AI-Powered Mental Health Prediction System  using Python Machine Learning (ML)

1. Download the zip record of the AI-Powered-Mental-Health-Prediction-ML-Projectin Python

2. Extract the file, copy Mental_Health_Prediction the files and paste it connected the desktop

3. Open PyCharm and import the task into PyCharm

4. Install 4 libraries (if not installed)

5. Run the Project utilizing the pursuing command

python manage.py runserver

Now, click the URL http://127.0.0.1:800,0 and the Project will run

Login Details

*************User************

Username:  john123

Password: Test@123

Or registry a caller user.

AI-Powered Mental Health Prediction System in Python & ML: Project Demo

AI-Powered Mental Health Prediction System in Python & ML: Project, Report, and PPT