7.1 Training Data

Used to teach the AI

Example:

  • 80% of data

7.2 Testing Data

Used to check AI accuracy

Example:

  • 20% of data

7.3 Student Analogy

StudentAI
BooksTraining data
ExamTesting data
MarksAccuracy

8. Accuracy, Errors, and Improvement

  • Accuracy = Correct predictions

  • Error = Wrong prediction

  • More data + better model = higher accuracy

9. Common Student Confusions (Very Important)

❌ AI is not magic
❌ AI is not human
❌ AI does not think emotionally
❌ AI depends fully on data

One-Page Ultimate Summary

  • AI → Intelligence in machines

  • ML → Learning from data

  • DL → Brain-like learning

  • Data → Fuel

  • Algorithm → Steps

  • Model → Learned brain

  • Training → Learning

  • Testing → Checking

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