AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 617 · 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 flagging a new email? (a) the learned patterns (b) flagging a new email
2. 2.True or false: “labelled fruit photos” is training data. (a) True (b) False
3. 3.Which of these is a prediction? (a) the learned patterns (b) old emails marked spam (c) recorded spoken words (d) flagging a new email
4. 4.True or false: “500 labelled leaf photos” is a prediction. (a) True (b) False
5. 5.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
6. 6.Which of these is the model? (a) naming a new leaf (b) typing a new spoken word (c) tomorrow’s rain guess (d) what training builds
7. 7.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
8. 8.Which of these is a prediction? (a) recorded spoken words (b) old emails marked spam (c) past weather records (d) tomorrow’s rain guess
9. 9.⏩ In machine learning, which comes first: labelled fruit photos or the trained program? (a) labelled fruit photos (b) the trained program
10. 10.⏩ In machine learning, which comes first: 500 labelled leaf photos or naming a new leaf? (a) 500 labelled leaf photos (b) naming a new leaf
11. 11.🔁 What is the right order? (a) model, prediction, data (b) prediction, data, model (c) data, prediction, model (d) data, model, prediction
12. 12.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) the model (c) a prediction
13. 13.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
14. 14.True or false: “naming a new leaf” is a prediction. (a) False (b) True
15. 15.⏩ In machine learning, which comes first: recorded spoken words or naming a new leaf? (a) recorded spoken words (b) naming a new leaf
16. 16.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
17. 17.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a label error (c) a prediction (d) a password
18. 18.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) a prediction (c) the model
19. 19.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
20. 20.True or false: “recorded spoken words” is the model. (a) True (b) False
21. 21.True or false: “recorded spoken words” is training data. (a) True (b) False
22. 22.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
23. 23.Which of these is training data? (a) the learned patterns (b) the trained program (c) tomorrow’s rain guess (d) 500 labelled leaf photos
24. 24.⏩ In machine learning, which comes first: what training builds or old emails marked spam? (a) what training builds (b) old emails marked spam
25. 25.Which of these is a prediction? (a) naming a new leaf (b) past weather records (c) the trained program (d) what training builds
26. 26.Which of these is the model? (a) flagging a new email (b) old emails marked spam (c) the learned patterns (d) tomorrow’s rain guess
27. 27.⏩ 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
28. 28.⏩ In machine learning, which comes first: typing a new spoken word or the learned patterns? (a) typing a new spoken word (b) the learned patterns
29. 29.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
30. 30.⏩ In machine learning, which comes first: 500 labelled leaf photos or the trained program? (a) 500 labelled leaf photos (b) the trained program
31. 31.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to see if it works (d) to make it slower
32. 32.⏩ In machine learning, which comes first: 500 labelled leaf photos or typing a new spoken word? (a) 500 labelled leaf photos (b) typing a new spoken word
33. 33.⏩ In machine learning, which comes first: tomorrow’s rain guess or 500 labelled leaf photos? (a) tomorrow’s rain guess (b) 500 labelled leaf photos
34. 34.⏩ 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
35. 35.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) training data (c) the model
36. 36.Which of these is a prediction? (a) naming a new fruit photo (b) recorded spoken words (c) the learned patterns (d) 500 labelled leaf photos
37. 37.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
38. 38.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
39. 39.📦 What happens during training? (a) it charges up (b) it prints labels (c) it learns patterns (d) it takes photos
40. 40.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam

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