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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 219 · 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.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) a prediction (c) the model
  2. 2.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess
  3. 3.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  4. 4.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  5. 5.⏩ In machine learning, which comes first: naming a new fruit photo or labelled fruit photos? (a) naming a new fruit photo (b) labelled fruit photos
  6. 6.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  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.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction
  9. 9.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program
  10. 10.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
  11. 11.Which of these is a prediction? (a) recorded spoken words (b) labelled fruit photos (c) naming a new leaf (d) the trained program
  12. 12.🔁 What is the right order? (a) prediction, data, model (b) data, model, prediction (c) model, prediction, data (d) data, prediction, model
  13. 13.⏩ In machine learning, which comes first: labelled fruit photos or tomorrow’s rain guess? (a) labelled fruit photos (b) tomorrow’s rain guess
  14. 14.True or false: “past weather records” is training data. (a) False (b) True
  15. 15.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) training data (c) the model
  16. 16.Which of these is a prediction? (a) flagging a new email (b) old emails marked spam (c) labelled fruit photos (d) the learned patterns
  17. 17.Which of these is training data? (a) naming a new leaf (b) labelled fruit photos (c) naming a new fruit photo (d) the learned patterns
  18. 18.⏩ In machine learning, which comes first: typing a new spoken word or labelled fruit photos? (a) typing a new spoken word (b) labelled fruit photos
  19. 19.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) the model (c) training data
  20. 20.⏩ In machine learning, which comes first: past weather records or naming a new leaf? (a) past weather records (b) naming a new leaf
  21. 21.Which of these is the model? (a) typing a new spoken word (b) naming a new fruit photo (c) labelled fruit photos (d) the learned patterns
  22. 22.True or false: “the learned patterns” is the model. (a) False (b) True
  23. 23.🧪 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
  24. 24.Which of these is a prediction? (a) the learned patterns (b) past weather records (c) the trained program (d) tomorrow’s rain guess
  25. 25.📦 What happens during training? (a) it learns patterns (b) it charges up (c) it takes photos (d) it prints labels
  26. 26.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
  27. 27.Which of these is the model? (a) old emails marked spam (b) recorded spoken words (c) labelled fruit photos (d) the trained program
  28. 28.Which of these is training data? (a) naming a new fruit photo (b) what training builds (c) recorded spoken words (d) the learned patterns
  29. 29.Which of these is training data? (a) naming a new leaf (b) past weather records (c) tomorrow’s rain guess (d) what training builds
  30. 30.⏩ 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
  31. 31.True or false: “labelled fruit photos” is training data. (a) False (b) True
  32. 32.Which of these is training data? (a) what training builds (b) the trained program (c) 500 labelled leaf photos (d) flagging a new email
  33. 33.Which of these is training data? (a) old emails marked spam (b) tomorrow’s rain guess (c) the trained program (d) naming a new leaf
  34. 34.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  35. 35.True or false: “old emails marked spam” is a prediction. (a) True (b) False
  36. 36.⏩ In machine learning, which comes first: the trained program or labelled fruit photos? (a) the trained program (b) labelled fruit photos
  37. 37.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) training data (c) a prediction
  38. 38.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  39. 39.True or false: “what training builds” is a prediction. (a) False (b) True
  40. 40.True or false: “the trained program” is a prediction. (a) False (b) True

Answer key

  1. training data
  2. what training builds
  3. the trained program
  4. True
  5. labelled fruit photos
  6. a prediction
  7. what training builds
  8. the model
  9. the trained program
  10. training data
  11. naming a new leaf
  12. data, model, prediction
  13. labelled fruit photos
  14. True
  15. the model
  16. flagging a new email
  17. labelled fruit photos
  18. labelled fruit photos
  19. a prediction
  20. past weather records
  21. the learned patterns
  22. True
  23. to see if it works
  24. tomorrow’s rain guess
  25. it learns patterns
  26. the model
  27. the trained program
  28. recorded spoken words
  29. past weather records
  30. the trained program
  31. True
  32. 500 labelled leaf photos
  33. old emails marked spam
  34. a prediction
  35. False
  36. labelled fruit photos
  37. training data
  38. training data
  39. False
  40. False

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