AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 546 · 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: 500 labelled leaf photos or naming a new fruit photo? (a) 500 labelled leaf photos (b) naming a new fruit photo
2. 2.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
3. 3.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
4. 4.Which of these is the model? (a) labelled fruit photos (b) naming a new leaf (c) the learned patterns (d) typing a new spoken word
5. 5.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
6. 6.⏩ In machine learning, which comes first: labelled fruit photos or naming a new leaf? (a) labelled fruit photos (b) naming a new leaf
7. 7.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) training data (c) a prediction
8. 8.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to see if it works (d) to change its name
9. 9.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
10. 10.📦 What happens during training? (a) it takes photos (b) it learns patterns (c) it prints labels (d) it charges up
11. 11.Which of these is the model? (a) past weather records (b) what training builds (c) flagging a new email (d) recorded spoken words
12. 12.True or false: “flagging a new email” is a prediction. (a) True (b) False
13. 13.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) the model (c) a prediction
14. 14.⏩ 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
15. 15.True or false: “the trained program” is training data. (a) True (b) False
16. 16.Which of these is training data? (a) typing a new spoken word (b) labelled fruit photos (c) the trained program (d) tomorrow’s rain guess
17. 17.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
18. 18.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
19. 19.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
20. 20.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
21. 21.Which of these is training data? (a) the trained program (b) old emails marked spam (c) flagging a new email (d) naming a new leaf
22. 22.True or false: “tomorrow’s rain guess” is training data. (a) True (b) False
23. 23.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
24. 24.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
25. 25.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False
26. 26.Which of these is the model? (a) 500 labelled leaf photos (b) the trained program (c) naming a new fruit photo (d) flagging a new email
27. 27.Which of these is a prediction? (a) the trained program (b) the learned patterns (c) past weather records (d) typing a new spoken word
28. 28.⏩ In machine learning, which comes first: naming a new fruit photo or old emails marked spam? (a) naming a new fruit photo (b) old emails marked spam
29. 29.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a label error (c) a password (d) training data
30. 30.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) data, prediction, model (d) model, prediction, data
31. 31.⏩ 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
32. 32.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
33. 33.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
34. 34.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
35. 35.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) training data (c) the model
36. 36.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
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: “old emails marked spam”? (a) the model (b) training data (c) a prediction
39. 39.True or false: “old emails marked spam” is the model. (a) True (b) False
40. 40.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model

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