Spam Text Detection
Simple web application to detect whether given text is a spam or not
With the exponential growth of digital communication, email and messaging platforms have become indispensable tools for both personal and professional interactions. However, this widespread usage has also led to an overwhelming influx of unwanted or malicious content, commonly referred to as spam. Spam messages not only clutter inboxes but often pose significant risks, such as phishing attacks or malware distribution. To address this challenge, automated systems for spam detection have become a necessity. These systems aim to classify text as either spam or legitimate content, enabling users to maintain secure and organized communication channels. This project focuses on leveraging Naive Bayes algorithm to determine whether a given text is spam or not, offering a robust solution to enhance digital safety and efficiency. Note: This was a learning experience to implement a full-stack application with front-end done in reactJS and backend in Django.
The project can be accessed at:
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https://github.com/chengq220/spam_filter
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