Inspiration
Spam messages are a daily nuisance, from promotions to phishing scams. I wanted to create an app that helps users instantly detect spam.
What it does
SpamShield is an AI-powered SMS spam detector that classifies messages as spam or ham (not spam) in real-time.
How we built it
We used Python, Scikit-learn, and NLTK for machine learning and text preprocessing. The user-friendly interface was built with Streamlit.
Challenges we ran into
Improving text preprocessing and balancing precision-recall was tricky. Optimizing the web interface for real-time detection was also a challenge.
Accomplishments that we're proud of
We built a high-accuracy spam detection model and a smooth, interactive web app for real-time analysis.
What we learned
We gained experience in text preprocessing, deploying ML models, and handling imbalanced datasets for better classification.
What's next for SpamShield
We plan to integrate deep learning, real-time SMS monitoring, phishing detection, and a mobile app version.
Built With
- csv
- jupiter
- plk
- python
- typescript
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