AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 519 · 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.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
2. 2.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
3. 3.Which of these is a prediction? (a) old emails marked spam (b) recorded spoken words (c) naming a new leaf (d) past weather records
4. 4.Which of these is the model? (a) naming a new fruit photo (b) 500 labelled leaf photos (c) labelled fruit photos (d) the learned patterns
5. 5.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a label error (c) a password (d) a prediction
6. 6.⏩ In machine learning, which comes first: past weather records or tomorrow’s rain guess? (a) past weather records (b) tomorrow’s rain guess
7. 7.True or false: “what training builds” is the model. (a) False (b) True
8. 8.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
9. 9.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
10. 10.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
11. 11.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
12. 12.📦 What happens during training? (a) it charges up (b) it takes photos (c) it learns patterns (d) it prints labels
13. 13.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) training data (c) the model
14. 14.⏩ In machine learning, which comes first: 500 labelled leaf photos or the trained program? (a) 500 labelled leaf photos (b) the trained program
15. 15.⏩ In machine learning, which comes first: the trained program or typing a new spoken word? (a) the trained program (b) typing a new spoken word
16. 16.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program
17. 17.⏩ In machine learning, which comes first: the learned patterns or naming a new fruit photo? (a) the learned patterns (b) naming a new fruit photo
18. 18.True or false: “past weather records” is the model. (a) True (b) False
19. 19.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
20. 20.True or false: “past weather records” is training data. (a) False (b) True
21. 21.Which of these is a prediction? (a) the trained program (b) what training builds (c) 500 labelled leaf photos (d) flagging a new email
22. 22.Which of these is training data? (a) naming a new leaf (b) naming a new fruit photo (c) the trained program (d) past weather records
23. 23.Which of these is a prediction? (a) old emails marked spam (b) 500 labelled leaf photos (c) labelled fruit photos (d) tomorrow’s rain guess
24. 24.🔁 What is the right order? (a) data, model, prediction (b) data, prediction, model (c) prediction, data, model (d) model, prediction, data
25. 25.⏩ In machine learning, which comes first: labelled fruit photos or typing a new spoken word? (a) labelled fruit photos (b) typing a new spoken word
26. 26.Which of these is a prediction? (a) the trained program (b) recorded spoken words (c) old emails marked spam (d) naming a new fruit photo
27. 27.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
28. 28.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
29. 29.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) a prediction (c) training data
30. 30.⏩ In machine learning, which comes first: what training builds or past weather records? (a) what training builds (b) past weather records
31. 31.🧪 Why test a model on NEW examples? (a) to delete its data (b) to see if it works (c) to change its name (d) to make it slower
32. 32.True or false: “old emails marked spam” is training data. (a) True (b) False
33. 33.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
34. 34.Which of these is the model? (a) flagging a new email (b) naming a new leaf (c) naming a new fruit photo (d) what training builds
35. 35.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess
36. 36.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) a prediction (c) training data
37. 37.True or false: “flagging a new email” is the model. (a) False (b) True
38. 38.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
39. 39.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
40. 40.⏩ In machine learning, which comes first: 500 labelled leaf photos or flagging a new email? (a) 500 labelled leaf photos (b) flagging a new email

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