Web3 Personality Analyser

Welcome to the Web3 Personality Analyser! This web app is built with an open-source philosophy, enabling anyone to customize and enhance it. Our goal is to facilitate the detection of mental health problems using advanced machine learning techniques.

Overview

The Web3 Personality Analyser leverages Web3 technology to provide easy access to datasets and machine learning models. By simply running a Python script, users can download the dataset and build a model, thanks to the integration with 0g Labs. We employ a RandomForestClassifier for our machine learning model, which achieves an impressive accuracy rate of over 95%.

Features

• Open Source: Customize and enhance the app to fit your needs.
• Mental Health Detection: Focuses on detecting mental health issues.
• Web3 Integration: Easily access datasets and build models.
• Machine Learning: Utilizes RandomForestClassifier with >95% accuracy.

Getting Started

Prerequisites

• Python 3.x
• Go

Installation

1. Clone the repository:

   git clone https://github.com/skwasimrazzak/Web3-Personality-Analyser.git
   cd Web3-Personality-Analyser

2. Set up the Go module and run the Go script to upload the dataset:

   go mod init 0g-sdk-demo
   go mod tidy
   go run main.go

Usage

1. Run the Python script to download the dataset and build the model:

   python script.py

2. Start the web app (instructions depend on your web framework and setup).

Customization

Feel free to customize and enhance the app to better suit your requirements. Contributions are welcome!

Machine Learning Model

We use a RandomForestClassifier for our machine learning model, which provides an accuracy rate of over 95%.

Contributing

We welcome contributions from the community. If you have suggestions for improvements, please open an issue or submit a pull request.

Acknowledgements

• Powered by 0g Labs
• Thanks to the open-source community for their contributions