AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 83 · 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: the trained program or naming a new fruit photo? (a) the trained program (b) naming a new fruit photo
2. 2.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) data, prediction, model (d) model, prediction, data
3. 3.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) a prediction (c) training data
4. 4.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
5. 5.⏩ In machine learning, which comes first: 500 labelled leaf photos or naming a new fruit photo? (a) 500 labelled leaf photos (b) naming a new fruit photo
6. 6.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
7. 7.True or false: “naming a new fruit photo” is training data. (a) False (b) True
8. 8.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) a prediction (c) the model
9. 9.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
10. 10.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) training data (c) a prediction (d) a label error
11. 11.📦 What happens during training? (a) it charges up (b) it takes photos (c) it prints labels (d) it learns patterns
12. 12.True or false: “recorded spoken words” is training data. (a) False (b) True
13. 13.⏩ 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
14. 14.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) the model (c) a prediction
15. 15.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to delete its data (d) to see if it works
16. 16.Which of these is training data? (a) labelled fruit photos (b) naming a new fruit photo (c) naming a new leaf (d) tomorrow’s rain guess
17. 17.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
18. 18.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
19. 19.Which of these is training data? (a) naming a new leaf (b) past weather records (c) flagging a new email (d) naming a new fruit photo
20. 20.Which of these is a prediction? (a) old emails marked spam (b) 500 labelled leaf photos (c) tomorrow’s rain guess (d) the learned patterns
21. 21.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
22. 22.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
23. 23.True or false: “labelled fruit photos” is training data. (a) False (b) True
24. 24.Which of these is the model? (a) recorded spoken words (b) the trained program (c) past weather records (d) naming a new fruit photo
25. 25.True or false: “naming a new leaf” is the model. (a) True (b) False
26. 26.Which of these is a prediction? (a) old emails marked spam (b) the learned patterns (c) 500 labelled leaf photos (d) naming a new fruit photo
27. 27.⏩ 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
28. 28.True or false: “old emails marked spam” is the model. (a) False (b) True
29. 29.True or false: “naming a new leaf” is a prediction. (a) False (b) True
30. 30.Which of these is training data? (a) old emails marked spam (b) typing a new spoken word (c) flagging a new email (d) the trained program
31. 31.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
32. 32.⏩ In machine learning, which comes first: labelled fruit photos or what training builds? (a) labelled fruit photos (b) what training builds
33. 33.⏩ In machine learning, which comes first: typing a new spoken word or what training builds? (a) typing a new spoken word (b) what training builds
34. 34.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
35. 35.⏩ In machine learning, which comes first: recorded spoken words or the trained program? (a) recorded spoken words (b) the trained program
36. 36.Which of these is the model? (a) naming a new leaf (b) recorded spoken words (c) past weather records (d) what training builds
37. 37.Which of these is a prediction? (a) recorded spoken words (b) labelled fruit photos (c) what training builds (d) naming a new leaf
38. 38.⏩ In machine learning, which comes first: the trained program or recorded spoken words? (a) the trained program (b) recorded spoken words
39. 39.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
40. 40.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data

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