https://spam-detection-tool-1.onrender.com
https://youtu.be/5uzirp4B6rI?si=CwZNA23-iHx6bHXB
Title: Develop Spam alert tool
Description: Develop a tool that can analyse and verify the source of any incoming call, link, SMS, mms and Email based on the inputs from the user. The solution should be able to check is source is genuine or spam
The Spam Detection and Prevention Tool named as Rakshak is a project developed during a hackathon aimed at detecting and preventing spam across various communication channels. This tool provides users with the ability to detect spam messages, emails, multimedia messages (MMS), and short message service (SMS). Additionally, it includes functionality to determine whether phone numbers are associated with spam activity. Furthermore, the project integrates a chatbot where users can seek advice on how to stay safe from spam and fraud.
Utilizes machine learning models to detect spam messages, emails, MMS, and SMS.
Determines whether phone numbers are spam or legitimate.
Includes a chatbot interface where users can inquire about spam prevention methods and safety tips.
Utilizes Twilio API for spam call detection and prevention.
Python web framework used for building the application.
Programming language utilized for backend development and machine learning model implementation.
Implements machine learning algorithms for spam detection.
Integrates APIs for fetching data and enhancing spam detection capabilities.
Utilizes Twilio API for spam call detection and prevention.
1.) Clone the repository:
git clone https://github.com/Blacksujit/spam-detection-tool.git
2.) Install Dependencies:
pip install -r requirements.txt
3.) Run the Flask application:
python wsgi.py
1.) Sanskar Awati
2.) Abhishek Kute
MIT