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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 701 · 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.Which of these is the model? (a) the learned patterns (b) 500 labelled leaf photos (c) old emails marked spam (d) flagging a new email
  2. 2.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  3. 3.True or false: “old emails marked spam” is the model. (a) True (b) False
  4. 4.⏩ In machine learning, which comes first: what training builds or old emails marked spam? (a) what training builds (b) old emails marked spam
  5. 5.True or false: “labelled fruit photos” is training data. (a) False (b) True
  6. 6.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  7. 7.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program
  8. 8.⏩ 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
  9. 9.🧪 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
  10. 10.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  11. 11.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  12. 12.⏩ In machine learning, which comes first: old emails marked spam or flagging a new email? (a) old emails marked spam (b) flagging a new email
  13. 13.Which of these is training data? (a) typing a new spoken word (b) what training builds (c) flagging a new email (d) labelled fruit photos
  14. 14.🔁 What is the right order? (a) data, prediction, model (b) prediction, data, model (c) data, model, prediction (d) model, prediction, data
  15. 15.True or false: “recorded spoken words” is the model. (a) False (b) True
  16. 16.True or false: “the trained program” is a prediction. (a) True (b) False
  17. 17.📦 What happens during training? (a) it takes photos (b) it charges up (c) it prints labels (d) it learns patterns
  18. 18.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  19. 19.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) a prediction (c) training data
  20. 20.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  21. 21.Which of these is training data? (a) what training builds (b) flagging a new email (c) old emails marked spam (d) tomorrow’s rain guess
  22. 22.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  23. 23.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
  24. 24.True or false: “flagging a new email” is training data. (a) True (b) False
  25. 25.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  26. 26.True or false: “what training builds” is the model. (a) False (b) True
  27. 27.⏩ 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
  28. 28.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
  29. 29.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) training data (c) a prediction
  30. 30.Which of these is a prediction? (a) old emails marked spam (b) tomorrow’s rain guess (c) past weather records (d) 500 labelled leaf photos
  31. 31.True or false: “naming a new leaf” is training data. (a) True (b) False
  32. 32.Which of these is the model? (a) recorded spoken words (b) labelled fruit photos (c) the trained program (d) naming a new leaf
  33. 33.⏩ In machine learning, which comes first: 500 labelled leaf photos or flagging a new email? (a) 500 labelled leaf photos (b) flagging a new email
  34. 34.True or false: “flagging a new email” is the model. (a) True (b) False
  35. 35.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
  36. 36.Which of these is training data? (a) the learned patterns (b) 500 labelled leaf photos (c) naming a new fruit photo (d) what training builds
  37. 37.⏩ In machine learning, which comes first: the learned patterns or labelled fruit photos? (a) the learned patterns (b) labelled fruit photos
  38. 38.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  39. 39.True or false: “naming a new fruit photo” is the model. (a) False (b) True
  40. 40.Which of these is training data? (a) recorded spoken words (b) typing a new spoken word (c) what training builds (d) tomorrow’s rain guess

Answer key

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

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