AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 77 · 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: “recorded spoken words” is training data. (a) False (b) True
2. 2.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction
3. 3.True or false: “naming a new fruit photo” is the model. (a) False (b) True
4. 4.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) data, prediction, model (d) prediction, data, model
5. 5.True or false: “labelled fruit photos” is the model. (a) False (b) True
6. 6.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) training data (c) a prediction
7. 7.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
8. 8.Which of these is the model? (a) the learned patterns (b) 500 labelled leaf photos (c) naming a new leaf (d) old emails marked spam
9. 9.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
10. 10.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) training data (c) a label error (d) a password
11. 11.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
12. 12.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
13. 13.Which of these is training data? (a) tomorrow’s rain guess (b) recorded spoken words (c) naming a new fruit photo (d) the trained program
14. 14.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
15. 15.⏩ In machine learning, which comes first: past weather records or naming a new leaf? (a) past weather records (b) naming a new leaf
16. 16.⏩ 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
17. 17.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
18. 18.Which of these is training data? (a) naming a new leaf (b) 500 labelled leaf photos (c) flagging a new email (d) the trained program
19. 19.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
20. 20.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
21. 21.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
22. 22.🧪 Why test a model on NEW examples? (a) to make it slower (b) to delete its data (c) to change its name (d) to see if it works
23. 23.True or false: “flagging a new email” is a prediction. (a) False (b) True
24. 24.⏩ In machine learning, which comes first: typing a new spoken word or old emails marked spam? (a) typing a new spoken word (b) old emails marked spam
25. 25.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
26. 26.Which of these is training data? (a) naming a new fruit photo (b) past weather records (c) the learned patterns (d) the trained program
27. 27.Which of these is a prediction? (a) labelled fruit photos (b) what training builds (c) flagging a new email (d) 500 labelled leaf photos
28. 28.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
29. 29.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
30. 30.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
31. 31.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it takes photos (d) it prints labels
32. 32.Which of these is training data? (a) naming a new leaf (b) flagging a new email (c) naming a new fruit photo (d) labelled fruit photos
33. 33.True or false: “past weather records” is training data. (a) True (b) False
34. 34.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
35. 35.True or false: “old emails marked spam” is a prediction. (a) False (b) True
36. 36.True or false: “what training builds” is a prediction. (a) False (b) True
37. 37.Which of these is a prediction? (a) old emails marked spam (b) naming a new leaf (c) past weather records (d) 500 labelled leaf photos
38. 38.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
39. 39.⏩ In machine learning, which comes first: what training builds or naming a new fruit photo? (a) what training builds (b) naming a new fruit photo
40. 40.Which of these is training data? (a) old emails marked spam (b) tomorrow’s rain guess (c) the learned patterns (d) naming a new fruit photo

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