Normal messages are correctly identified as Not Spam (HAM) with a high confidence score.
Spam messages are clearly flagged with a warning indicator and a confidence progress bar.
A Streamlit-based NLP Spam Message Detection application that classifies text messages as Spam or Not Spam (Ham) using Machine Learning.
🔗 Live Demo: 👉 https://nlp-spam-detector.streamlit.app/
✨ Features
🔍 Classifies messages as Spam or Not Spam (Ham)
📊 Displays confidence score (%) for predictions
📈 Visual confidence progress bar
🧠 Uses TF-IDF vectorization for text representation
🤖 Powered by a TensorFlow / Keras trained model
🎨 Clean and minimal Streamlit UI
☁️ Deployed on Streamlit Cloud
Text Preprocessing
Converts text to lowercase
Removes non-alphabet characters
Removes stopwords using NLTK
Applies Porter Stemming
Feature Extraction
Uses TF-IDF Vectorizer to convert text into numerical features
Prediction
A trained TensorFlow/Keras binary classification model
Outputs a probability score:
0.5 → Spam
≤ 0.5 → Not Spam (Ham)
Confidence Display
Prediction confidence shown as a percentage
Visualized using a progress bar for better UX
🛠️ Tech Stack Python Streamlit TensorFlow / Keras Scikit-learn NLTK Joblib NumPy
How to Run Locally
1️⃣ Clone the repository git clone https://github.com/ares-coding/spam-app.git cd spam-app
2️⃣ Install dependencies pip install -r requirements.txt
3️⃣ Run the app streamlit run app.py
🧪 Sample Test Messages ✅ Not Spam (Ham) Hi, are we still meeting later at 5pm?
🚨 Spam Congratulations! You won ₱50,000. Click the link now to claim your prize!
This application is for educational and demonstration purposes only. Prediction confidence does not guarantee absolute certainty.
⭐️ If you like this project
Feel free to star the repository and try the live demo!
👤 Author
Ares Coding GitHub: https://github.com/ares-coding