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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 660 · 40 questions
TalentJR

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.

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

Answer key

  1. it learns patterns
  2. to see if it works
  3. a prediction
  4. False
  5. data, model, prediction
  6. typing a new spoken word
  7. True
  8. old emails marked spam
  9. training data
  10. labelled fruit photos
  11. labelled fruit photos
  12. the learned patterns
  13. past weather records
  14. what training builds
  15. False
  16. old emails marked spam
  17. the learned patterns
  18. training data
  19. labelled fruit photos
  20. False
  21. recorded spoken words
  22. a prediction
  23. training data
  24. True
  25. training data
  26. what training builds
  27. True
  28. False
  29. True
  30. old emails marked spam
  31. naming a new leaf
  32. training data
  33. labelled fruit photos
  34. a prediction
  35. True
  36. True
  37. False
  38. the model
  39. naming a new fruit photo
  40. the learned patterns

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