AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 633 · 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 learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
2. 2.Which of these is training data? (a) labelled fruit photos (b) typing a new spoken word (c) naming a new leaf (d) tomorrow’s rain guess
3. 3.🔁 What is the right order? (a) model, prediction, data (b) data, prediction, model (c) prediction, data, model (d) data, model, prediction
4. 4.True or false: “old emails marked spam” is a prediction. (a) True (b) False
5. 5.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) training data (c) a prediction
6. 6.⏩ 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
7. 7.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
8. 8.⏩ 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
9. 9.Which of these is the model? (a) what training builds (b) old emails marked spam (c) flagging a new email (d) past weather records
10. 10.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
11. 11.📦 What happens during training? (a) it takes photos (b) it charges up (c) it prints labels (d) it learns patterns
12. 12.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
13. 13.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
14. 14.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
15. 15.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
16. 16.⏩ In machine learning, which comes first: labelled fruit photos or what training builds? (a) labelled fruit photos (b) what training builds
17. 17.True or false: “naming a new leaf” is training data. (a) True (b) False
18. 18.⏩ In machine learning, which comes first: what training builds or old emails marked spam? (a) what training builds (b) old emails marked spam
19. 19.⏩ In machine learning, which comes first: tomorrow’s rain guess or recorded spoken words? (a) tomorrow’s rain guess (b) recorded spoken words
20. 20.True or false: “naming a new leaf” is the model. (a) False (b) True
21. 21.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
22. 22.Which of these is a prediction? (a) what training builds (b) old emails marked spam (c) flagging a new email (d) the learned patterns
23. 23.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
24. 24.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
25. 25.🔮 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
26. 26.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
27. 27.⏩ In machine learning, which comes first: past weather records or naming a new leaf? (a) past weather records (b) naming a new leaf
28. 28.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
29. 29.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
30. 30.🧪 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
31. 31.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
32. 32.Which of these is training data? (a) naming a new leaf (b) what training builds (c) recorded spoken words (d) typing a new spoken word
33. 33.⏩ In machine learning, which comes first: the learned patterns or typing a new spoken word? (a) the learned patterns (b) typing a new spoken word
34. 34.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
35. 35.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
36. 36.⏩ 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
37. 37.True or false: “the trained program” is the model. (a) True (b) False
38. 38.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) the model (c) a prediction
39. 39.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
40. 40.Which of these is a prediction? (a) tomorrow’s rain guess (b) 500 labelled leaf photos (c) the learned patterns (d) recorded spoken words

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