The Email Spam Detector is a web application designed to identify whether an email message is spam. It features user authentication and utilizes machine learning algorithms to achieve high accuracy in spam detection.
Dataset Name: Spam Email Dataset Link: https://www.kaggle.com/datasets/jackksoncsie/spam-email-dataset
This dataset contains a collection of email text messages, labeled as either spam or not spam. Each email message is associated with a binary label, where "1" indicates that the email is spam, and "0" indicates that it is not spam. The dataset is intended for use in training and evaluating spam email classification models.
text (Text): This column contains the text content of the email messages. It includes the body of the emails along with any associated subject lines or headers.
spam_or_not (Binary): This column contains binary labels to indicate whether an email is spam or not. "1" represents spam, while "0" represents not spam.
- Open your web browser and go to http://127.0.0.1:5000.
- Sign up for a new account or log in with your existing credentials.
- Enter an email message to check if it is spam or not.
- View the results of the spam detection.
- User authentication with login and signup functionality.
- Real-time spam detection for email messages.
- Utilizes a Random Forest algorithm for high accuracy in spam detection.
- Easy-to-use web interface built with Flask, JavaScript, HTML, and CSS.
- Includes automated unit tests to verify predictions before merging branches to the main branch.
Contributions are always welcome!
Please see contributing.md for ways to get started.
Distributed under the MIT License. See LICENSE for more information.
- Kizhakkeppattu Rahul Govindkumar
- Email: krahulgovind@gmail.com
- Github: https://github.com/rahulorihiki