AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 589 · 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.True or false: “the trained program” is the model. (a) False (b) True
2. 2.Which of these is a prediction? (a) recorded spoken words (b) old emails marked spam (c) naming a new fruit photo (d) 500 labelled leaf photos
3. 3.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it takes photos (d) it prints labels
4. 4.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
5. 5.Which of these is a prediction? (a) flagging a new email (b) old emails marked spam (c) past weather records (d) labelled fruit photos
6. 6.Which of these is training data? (a) past weather records (b) naming a new fruit photo (c) the trained program (d) typing a new spoken word
7. 7.Which of these is training data? (a) flagging a new email (b) the trained program (c) labelled fruit photos (d) tomorrow’s rain guess
8. 8.True or false: “flagging a new email” is training data. (a) True (b) False
9. 9.True or false: “the learned patterns” is the model. (a) True (b) False
10. 10.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
11. 11.⏩ In machine learning, which comes first: flagging a new email or labelled fruit photos? (a) flagging a new email (b) labelled fruit photos
12. 12.True or false: “old emails marked spam” is training data. (a) True (b) False
13. 13.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
14. 14.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
15. 15.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, prediction, model (d) data, model, prediction
16. 16.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
17. 17.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
18. 18.True or false: “the learned patterns” is training data. (a) False (b) True
19. 19.True or false: “old emails marked spam” is the model. (a) True (b) False
20. 20.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
21. 21.Which of these is training data? (a) flagging a new email (b) recorded spoken words (c) what training builds (d) the learned patterns
22. 22.⏩ In machine learning, which comes first: past weather records or flagging a new email? (a) past weather records (b) flagging a new email
23. 23.True or false: “the trained program” is training data. (a) True (b) False
24. 24.True or false: “old emails marked spam” is a prediction. (a) True (b) False
25. 25.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
26. 26.⏩ In machine learning, which comes first: flagging a new email or 500 labelled leaf photos? (a) flagging a new email (b) 500 labelled leaf photos
27. 27.⏩ In machine learning, which comes first: what training builds or 500 labelled leaf photos? (a) what training builds (b) 500 labelled leaf photos
28. 28.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
29. 29.🧪 Why test a model on NEW examples? (a) to see if it works (b) to make it slower (c) to delete its data (d) to change its name
30. 30.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a prediction (c) a label error (d) training data
31. 31.Which of these is a prediction? (a) old emails marked spam (b) the trained program (c) past weather records (d) tomorrow’s rain guess
32. 32.⏩ In machine learning, which comes first: past weather records or naming a new fruit photo? (a) past weather records (b) naming a new fruit photo
33. 33.Which of these is the model? (a) what training builds (b) recorded spoken words (c) tomorrow’s rain guess (d) old emails marked spam
34. 34.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) training data (c) the model
35. 35.⏩ In machine learning, which comes first: the trained program or 500 labelled leaf photos? (a) the trained program (b) 500 labelled leaf photos
36. 36.True or false: “naming a new fruit photo” is the model. (a) True (b) False
37. 37.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
38. 38.Which of these is a prediction? (a) old emails marked spam (b) recorded spoken words (c) what training builds (d) typing a new spoken word
39. 39.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
40. 40.⏩ In machine learning, which comes first: the learned patterns or typing a new spoken word? (a) the learned patterns (b) typing a new spoken word

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