| # Spam / Not Spam Classifier | |
| A simple machine learning model built using **Logistic Regression + TF-IDF** to detect spam messages. | |
| --- | |
| ## How it works | |
| - Input: Raw text message | |
| - Preprocessing: TF-IDF Vectorizer | |
| - Model: Logistic Regression | |
| - Output: `spam` or `ham` | |
| --- | |
| ## Files included | |
| - `model.pkl` — trained ML model | |
| - `vectorizer.pkl` — TF-IDF vectorizer | |
| - `inference.py` — simple inference script | |
| --- | |
| ## Example Usage | |
| ```python | |
| from inference import predict | |
| print(predict("You have won $1000!!!")) | |