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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 52 · 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.⏩ 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
  2. 2.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  3. 3.Which of these is the model? (a) old emails marked spam (b) typing a new spoken word (c) recorded spoken words (d) the learned patterns
  4. 4.True or false: “naming a new leaf” is the model. (a) False (b) True
  5. 5.Which of these is a prediction? (a) labelled fruit photos (b) naming a new fruit photo (c) the learned patterns (d) what training builds
  6. 6.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  7. 7.⏩ 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
  8. 8.Which of these is a prediction? (a) old emails marked spam (b) labelled fruit photos (c) past weather records (d) tomorrow’s rain guess
  9. 9.True or false: “naming a new leaf” is training data. (a) False (b) True
  10. 10.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) the model (c) training data
  11. 11.Which of these is training data? (a) naming a new leaf (b) old emails marked spam (c) typing a new spoken word (d) what training builds
  12. 12.True or false: “the learned patterns” is training data. (a) False (b) True
  13. 13.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  14. 14.Which of these is the model? (a) naming a new fruit photo (b) typing a new spoken word (c) recorded spoken words (d) what training builds
  15. 15.True or false: “the learned patterns” is the model. (a) True (b) False
  16. 16.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) a prediction (c) the model
  17. 17.True or false: “old emails marked spam” is training data. (a) False (b) True
  18. 18.True or false: “naming a new leaf” is a prediction. (a) True (b) False
  19. 19.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  20. 20.⏩ 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
  21. 21.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  22. 22.⏩ 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
  23. 23.⏩ 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
  24. 24.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  25. 25.Which of these is training data? (a) tomorrow’s rain guess (b) flagging a new email (c) typing a new spoken word (d) recorded spoken words
  26. 26.Which of these is a prediction? (a) old emails marked spam (b) the trained program (c) past weather records (d) typing a new spoken word
  27. 27.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) model, prediction, data (d) data, model, prediction
  28. 28.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  29. 29.True or false: “past weather records” is a prediction. (a) False (b) True
  30. 30.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  31. 31.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
  32. 32.Which of these is training data? (a) past weather records (b) naming a new leaf (c) the learned patterns (d) typing a new spoken word
  33. 33.True or false: “labelled fruit photos” is training data. (a) True (b) False
  34. 34.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  35. 35.True or false: “naming a new fruit photo” is the model. (a) True (b) False
  36. 36.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a password (c) a label error (d) a prediction
  37. 37.True or false: “past weather records” is training data. (a) True (b) False
  38. 38.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) the model (c) a prediction
  39. 39.Which of these is training data? (a) tomorrow’s rain guess (b) naming a new fruit photo (c) labelled fruit photos (d) naming a new leaf
  40. 40.True or false: “old emails marked spam” is a prediction. (a) False (b) True

Answer key

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

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