AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 273 · 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: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
2. 2.True or false: “past weather records” is training data. (a) False (b) True
3. 3.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) training data (c) the model
4. 4.Which of these is training data? (a) flagging a new email (b) recorded spoken words (c) the trained program (d) what training builds
5. 5.📦 What happens during training? (a) it charges up (b) it takes photos (c) it learns patterns (d) it prints labels
6. 6.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
7. 7.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
8. 8.True or false: “the learned patterns” is training data. (a) False (b) True
9. 9.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
10. 10.⏩ In machine learning, which comes first: labelled fruit photos or flagging a new email? (a) labelled fruit photos (b) flagging a new email
11. 11.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a label error (c) training data (d) a password
12. 12.⏩ 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
13. 13.⏩ 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
14. 14.Which of these is the model? (a) recorded spoken words (b) typing a new spoken word (c) the learned patterns (d) flagging a new email
15. 15.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
16. 16.⏩ 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
17. 17.Which of these is the model? (a) labelled fruit photos (b) what training builds (c) recorded spoken words (d) 500 labelled leaf photos
18. 18.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
19. 19.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to delete its data (d) to change its name
20. 20.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
21. 21.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
22. 22.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) training data (c) the model
23. 23.True or false: “the trained program” is training data. (a) False (b) True
24. 24.Which of these is training data? (a) typing a new spoken word (b) what training builds (c) past weather records (d) naming a new fruit photo
25. 25.True or false: “naming a new leaf” is a prediction. (a) True (b) False
26. 26.⏩ 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
27. 27.True or false: “flagging a new email” is the model. (a) False (b) True
28. 28.⏩ 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
29. 29.True or false: “recorded spoken words” is training data. (a) True (b) False
30. 30.True or false: “what training builds” is the model. (a) False (b) True
31. 31.⏩ In machine learning, which comes first: the learned patterns or labelled fruit photos? (a) the learned patterns (b) labelled fruit photos
32. 32.⏩ In machine learning, which comes first: what training builds or typing a new spoken word? (a) what training builds (b) typing a new spoken word
33. 33.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
34. 34.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
35. 35.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
36. 36.Which of these is training data? (a) flagging a new email (b) 500 labelled leaf photos (c) tomorrow’s rain guess (d) the learned patterns
37. 37.⏩ In machine learning, which comes first: naming a new fruit photo or the learned patterns? (a) naming a new fruit photo (b) the learned patterns
38. 38.⏩ In machine learning, which comes first: the trained program or typing a new spoken word? (a) the trained program (b) typing a new spoken word
39. 39.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) training data (c) the model
40. 40.True or false: “500 labelled leaf photos” is training data. (a) False (b) True

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students