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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 390 · 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.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to see if it works (d) to change its name
  2. 2.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  3. 3.Which of these is training data? (a) what training builds (b) the learned patterns (c) recorded spoken words (d) typing a new spoken word
  4. 4.True or false: “naming a new leaf” is a prediction. (a) False (b) True
  5. 5.⏩ In machine learning, which comes first: flagging a new email or labelled fruit photos? (a) flagging a new email (b) labelled fruit photos
  6. 6.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, prediction, model (d) data, model, prediction
  7. 7.True or false: “500 labelled leaf photos” is a prediction. (a) True (b) False
  8. 8.True or false: “the learned patterns” is the model. (a) True (b) False
  9. 9.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  10. 10.True or false: “labelled fruit photos” is the model. (a) True (b) False
  11. 11.Which of these is the model? (a) tomorrow’s rain guess (b) labelled fruit photos (c) 500 labelled leaf photos (d) the trained program
  12. 12.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  13. 13.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  14. 14.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
  15. 15.Which of these is the model? (a) labelled fruit photos (b) tomorrow’s rain guess (c) naming a new leaf (d) what training builds
  16. 16.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  17. 17.Which of these is a prediction? (a) what training builds (b) the trained program (c) the learned patterns (d) tomorrow’s rain guess
  18. 18.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a password (c) a prediction (d) a label error
  19. 19.True or false: “naming a new leaf” is training data. (a) False (b) True
  20. 20.⏩ In machine learning, which comes first: the trained program or naming a new fruit photo? (a) the trained program (b) naming a new fruit photo
  21. 21.Which of these is training data? (a) tomorrow’s rain guess (b) naming a new fruit photo (c) the trained program (d) labelled fruit photos
  22. 22.True or false: “recorded spoken words” is training data. (a) True (b) False
  23. 23.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  24. 24.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
  25. 25.True or false: “the trained program” is the model. (a) False (b) True
  26. 26.True or false: “old emails marked spam” is the model. (a) True (b) False
  27. 27.⏩ In machine learning, which comes first: recorded spoken words or naming a new fruit photo? (a) recorded spoken words (b) naming a new fruit photo
  28. 28.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  29. 29.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  30. 30.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) a prediction (c) the model
  31. 31.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) training data (c) the model
  32. 32.Which of these is a prediction? (a) what training builds (b) past weather records (c) naming a new fruit photo (d) the trained program
  33. 33.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  34. 34.Which of these is the model? (a) 500 labelled leaf photos (b) naming a new fruit photo (c) old emails marked spam (d) the learned patterns
  35. 35.⏩ 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
  36. 36.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
  37. 37.Which of these is training data? (a) 500 labelled leaf photos (b) naming a new leaf (c) typing a new spoken word (d) what training builds
  38. 38.⏩ 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
  39. 39.Which of these is a prediction? (a) typing a new spoken word (b) old emails marked spam (c) the learned patterns (d) recorded spoken words
  40. 40.True or false: “labelled fruit photos” is training data. (a) True (b) False

Answer key

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

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