📧 Machine Learning Email / SMS Spam Detection

A simple Machine Learning project that detects spam vs ham (not spam) messages using text classification techniques in Python with scikit-learn.

This project demonstrates a complete ML pipeline including data loading, text preprocessing, feature extraction, model training, and prediction.

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🚀 Features

• Spam detection using Naive Bayes
• Text vectorization using TF-IDF
• Supports SMS / Email-style text
• Beginner-friendly implementation
• Fast and lightweight execution

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🧠 Machine Learning Workflow

1. Load the SMS Spam dataset
2. Preprocess and clean text
3. Convert text into numerical features (TF-IDF)
4. Train a classification model
5. Predict spam or ham messages

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📂 Project Structure

MACHINE-LEARNING-EMAIL-SPAM-DETECTION/
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├── spam_detector.py          # Main Python script for training & prediction
├── sample_sms.csv            # Sample SMS dataset
├── SMSSpamCollection         # Full SMS Spam Collection dataset
├── smsspamcollection.zip     # Zipped version of dataset
├── requirements.txt          # Project dependencies
├── run.log                   # Program execution logs
├── README.md                 # Project documentation