Spam Message Classification

This is a simple NLP machine learning project for detecting spam messages.

The project uses SMS text messages and trains a Naive Bayes model to classify messages as spam or ham.

What I practiced

• Loading text datasets with Pandas
• NLP preprocessing
• CountVectorizer
• Converting text into numerical features
• Train/test split
• Training a Naive Bayes classifier
• Model evaluation
• Saving the trained model

Libraries

• Pandas
• Scikit-learn
• Seaborn
• Matplotlib
• Joblib

Models Used

• CountVectorizer
• Multinomial Naive Bayes

Result

The model achieved around 98% accuracy on the test dataset.

Files

• main.ipynb
• spam_classifier.pkl
• vectorizer.pkl

Notes

This project was built for practicing NLP and text classification basics.