AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 572 · 40 questions

AI tip (Data → model → prediction): Training data = the examples (500 labelled leaf photos, old emails marked spam). The model = the learned patterns that training builds. A prediction = the model’s answer about something NEW (naming a new leaf, flagging a new email). The order is always data → model → prediction.

1. 1.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
2. 2.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a label error (c) training data (d) a prediction
3. 3.Which of these is the model? (a) recorded spoken words (b) flagging a new email (c) past weather records (d) what training builds
4. 4.True or false: “old emails marked spam” is the model. (a) True (b) False
5. 5.Which of these is the model? (a) the trained program (b) 500 labelled leaf photos (c) naming a new leaf (d) labelled fruit photos
6. 6.📦 What happens during training? (a) it prints labels (b) it takes photos (c) it charges up (d) it learns patterns
7. 7.True or false: “naming a new leaf” is the model. (a) True (b) False
8. 8.Which of these is training data? (a) the learned patterns (b) old emails marked spam (c) typing a new spoken word (d) the trained program
9. 9.True or false: “recorded spoken words” is training data. (a) False (b) True
10. 10.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) training data (c) the model
11. 11.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to make it slower (d) to see if it works
12. 12.🔁 What is the right order? (a) data, model, prediction (b) model, prediction, data (c) data, prediction, model (d) prediction, data, model
13. 13.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) training data (c) the model
14. 14.⏩ In machine learning, which comes first: old emails marked spam or flagging a new email? (a) old emails marked spam (b) flagging a new email
15. 15.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
16. 16.⏩ In machine learning, which comes first: naming a new fruit photo or past weather records? (a) naming a new fruit photo (b) past weather records
17. 17.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
18. 18.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
19. 19.True or false: “the learned patterns” is a prediction. (a) True (b) False
20. 20.⏩ In machine learning, which comes first: naming a new fruit photo or recorded spoken words? (a) naming a new fruit photo (b) recorded spoken words
21. 21.Which of these is a prediction? (a) 500 labelled leaf photos (b) labelled fruit photos (c) naming a new leaf (d) the learned patterns
22. 22.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) a prediction (c) the model
23. 23.Which of these is a prediction? (a) labelled fruit photos (b) recorded spoken words (c) the trained program (d) tomorrow’s rain guess
24. 24.True or false: “what training builds” is the model. (a) False (b) True
25. 25.Which of these is training data? (a) the learned patterns (b) 500 labelled leaf photos (c) the trained program (d) what training builds
26. 26.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
27. 27.True or false: “what training builds” is a prediction. (a) False (b) True
28. 28.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
29. 29.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
30. 30.True or false: “typing a new spoken word” is the model. (a) False (b) True
31. 31.⏩ In machine learning, which comes first: old emails marked spam or naming a new leaf? (a) old emails marked spam (b) naming a new leaf
32. 32.True or false: “naming a new fruit photo” is the model. (a) True (b) False
33. 33.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
34. 34.Which of these is a prediction? (a) the learned patterns (b) recorded spoken words (c) past weather records (d) flagging a new email
35. 35.True or false: “naming a new fruit photo” is a prediction. (a) False (b) True
36. 36.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) the model (c) a prediction
37. 37.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
38. 38.⏩ In machine learning, which comes first: the learned patterns or old emails marked spam? (a) the learned patterns (b) old emails marked spam
39. 39.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
40. 40.⏩ In machine learning, which comes first: flagging a new email or old emails marked spam? (a) flagging a new email (b) old emails marked spam

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