Machine Learning in Action

🛡️ Email Spam Detection

📧 1. Data Collection
🧠 2. Training Process
Features the Algorithm Learns
Urgent language ("NOW!", "URGENT!")
Money-related words ("$", "prize", "free")
Excessive punctuation ("!!!")
Suspicious sender addresses
All caps text
Generic greetings
Misspelled words
Call-to-action phrases
Learning Patterns
📊
Feature
Extraction
⚖️
Weight
Assignment
🎯
Pattern
Recognition
🔮 3. Prediction
New Email Arrives
Algorithm Analysis
Detected: Urgent language, promotional content, excessive punctuation, sales pressure
85% Confidence: SPAM
→ Moved to Spam Folder
✅ Result: Successful Classification
The model successfully identified spam characteristics and protected the user from unwanted content.