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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 233 · 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 is the right order? (a) data, model, prediction (b) data, prediction, model (c) model, prediction, data (d) prediction, data, model
  2. 2.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) the model (c) training data
  3. 3.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  4. 4.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  5. 5.True or false: “naming a new leaf” is the model. (a) False (b) True
  6. 6.True or false: “recorded spoken words” is the model. (a) False (b) True
  7. 7.Which of these is training data? (a) naming a new leaf (b) flagging a new email (c) the learned patterns (d) labelled fruit photos
  8. 8.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  9. 9.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
  10. 10.True or false: “old emails marked spam” is the model. (a) True (b) False
  11. 11.True or false: “the learned patterns” is training data. (a) False (b) True
  12. 12.⏩ 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
  13. 13.Which of these is training data? (a) recorded spoken words (b) naming a new fruit photo (c) typing a new spoken word (d) the trained program
  14. 14.⏩ In machine learning, which comes first: what training builds or labelled fruit photos? (a) what training builds (b) labelled fruit photos
  15. 15.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction
  16. 16.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  17. 17.📦 What happens during training? (a) it learns patterns (b) it takes photos (c) it prints labels (d) it charges up
  18. 18.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
  19. 19.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  20. 20.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) training data (c) a prediction
  21. 21.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  22. 22.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  23. 23.⏩ 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
  24. 24.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) the model (c) training data
  25. 25.⏩ 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
  26. 26.True or false: “recorded spoken words” is a prediction. (a) False (b) True
  27. 27.True or false: “what training builds” is the model. (a) False (b) True
  28. 28.⏩ 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
  29. 29.⏩ 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
  30. 30.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a password (c) training data (d) a label error
  31. 31.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  32. 32.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  33. 33.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
  34. 34.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  35. 35.True or false: “old emails marked spam” is training data. (a) False (b) True
  36. 36.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  37. 37.Which of these is training data? (a) old emails marked spam (b) what training builds (c) flagging a new email (d) the learned patterns
  38. 38.⏩ 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
  39. 39.⏩ In machine learning, which comes first: naming a new leaf or 500 labelled leaf photos? (a) naming a new leaf (b) 500 labelled leaf photos
  40. 40.True or false: “500 labelled leaf photos” is training data. (a) False (b) True

Answer key

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

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