AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 87 · 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.Which of these is training data? (a) naming a new leaf (b) 500 labelled leaf photos (c) the learned patterns (d) naming a new fruit photo
2. 2.Which of these is the model? (a) flagging a new email (b) recorded spoken words (c) tomorrow’s rain guess (d) the learned patterns
3. 3.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) training data (c) a prediction
4. 4.⏩ In machine learning, which comes first: typing a new spoken word or the trained program? (a) typing a new spoken word (b) the trained program
5. 5.⏩ In machine learning, which comes first: naming a new fruit photo or the trained program? (a) naming a new fruit photo (b) the trained program
6. 6.True or false: “recorded spoken words” is training data. (a) False (b) True
7. 7.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
8. 8.📦 What happens during training? (a) it prints labels (b) it charges up (c) it takes photos (d) it learns patterns
9. 9.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
10. 10.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
11. 11.⏩ In machine learning, which comes first: tomorrow’s rain guess or 500 labelled leaf photos? (a) tomorrow’s rain guess (b) 500 labelled leaf photos
12. 12.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) a prediction (c) training data
13. 13.Which of these is training data? (a) old emails marked spam (b) naming a new fruit photo (c) typing a new spoken word (d) naming a new leaf
14. 14.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
15. 15.Which of these is the model? (a) old emails marked spam (b) labelled fruit photos (c) naming a new fruit photo (d) the trained program
16. 16.🔁 What is the right order? (a) data, prediction, model (b) data, model, prediction (c) prediction, data, model (d) model, prediction, data
17. 17.Which of these is a prediction? (a) tomorrow’s rain guess (b) old emails marked spam (c) the learned patterns (d) the trained program
18. 18.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
19. 19.Which of these is a prediction? (a) labelled fruit photos (b) what training builds (c) naming a new leaf (d) 500 labelled leaf photos
20. 20.True or false: “past weather records” is training data. (a) False (b) True
21. 21.🧪 Why test a model on NEW examples? (a) to change its name (b) to see if it works (c) to delete its data (d) to make it slower
22. 22.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
23. 23.Which of these is the model? (a) naming a new leaf (b) old emails marked spam (c) labelled fruit photos (d) what training builds
24. 24.Which of these is training data? (a) flagging a new email (b) the learned patterns (c) labelled fruit photos (d) tomorrow’s rain guess
25. 25.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
26. 26.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
27. 27.True or false: “old emails marked spam” is the model. (a) False (b) True
28. 28.True or false: “tomorrow’s rain guess” is training data. (a) True (b) False
29. 29.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a prediction (c) a password (d) training data
30. 30.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
31. 31.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
32. 32.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
33. 33.⏩ In machine learning, which comes first: what training builds or labelled fruit photos? (a) what training builds (b) labelled fruit photos
34. 34.Which of these is a prediction? (a) labelled fruit photos (b) 500 labelled leaf photos (c) naming a new fruit photo (d) old emails marked spam
35. 35.True or false: “past weather records” is the model. (a) True (b) False
36. 36.True or false: “naming a new leaf” is a prediction. (a) False (b) True
37. 37.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
38. 38.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) training data (c) a prediction
39. 39.True or false: “recorded spoken words” is the model. (a) False (b) True
40. 40.True or false: “old emails marked spam” is training data. (a) True (b) False

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