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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 295 · 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.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  2. 2.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  3. 3.True or false: “the learned patterns” is training data. (a) False (b) True
  4. 4.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  5. 5.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a password (c) training data (d) a prediction
  6. 6.⏩ In machine learning, which comes first: tomorrow’s rain guess or old emails marked spam? (a) tomorrow’s rain guess (b) old emails marked spam
  7. 7.Which of these is training data? (a) recorded spoken words (b) the trained program (c) the learned patterns (d) naming a new fruit photo
  8. 8.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) a prediction (c) training data
  9. 9.Which of these is a prediction? (a) naming a new fruit photo (b) 500 labelled leaf photos (c) recorded spoken words (d) past weather records
  10. 10.Which of these is the model? (a) labelled fruit photos (b) old emails marked spam (c) what training builds (d) past weather records
  11. 11.⏩ In machine learning, which comes first: the trained program or recorded spoken words? (a) the trained program (b) recorded spoken words
  12. 12.True or false: “the trained program” is training data. (a) True (b) False
  13. 13.Which of these is a prediction? (a) 500 labelled leaf photos (b) past weather records (c) naming a new leaf (d) what training builds
  14. 14.True or false: “flagging a new email” is the model. (a) True (b) False
  15. 15.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  16. 16.Which of these is training data? (a) what training builds (b) typing a new spoken word (c) 500 labelled leaf photos (d) naming a new fruit photo
  17. 17.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) prediction, data, model (d) data, model, prediction
  18. 18.⏩ In machine learning, which comes first: what training builds or 500 labelled leaf photos? (a) what training builds (b) 500 labelled leaf photos
  19. 19.True or false: “the learned patterns” is a prediction. (a) True (b) False
  20. 20.True or false: “tomorrow’s rain guess” is training data. (a) True (b) False
  21. 21.⏩ In machine learning, which comes first: what training builds or typing a new spoken word? (a) what training builds (b) typing a new spoken word
  22. 22.Which of these is training data? (a) the trained program (b) labelled fruit photos (c) what training builds (d) naming a new fruit photo
  23. 23.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  24. 24.⏩ In machine learning, which comes first: labelled fruit photos or naming a new leaf? (a) labelled fruit photos (b) naming a new leaf
  25. 25.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  26. 26.⏩ In machine learning, which comes first: naming a new leaf or past weather records? (a) naming a new leaf (b) past weather records
  27. 27.True or false: “naming a new leaf” is a prediction. (a) True (b) False
  28. 28.⏩ In machine learning, which comes first: the trained program or flagging a new email? (a) the trained program (b) flagging a new email
  29. 29.True or false: “recorded spoken words” is the model. (a) False (b) True
  30. 30.🧪 Why test a model on NEW examples? (a) to delete its data (b) to change its name (c) to make it slower (d) to see if it works
  31. 31.True or false: “what training builds” is training data. (a) False (b) True
  32. 32.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
  33. 33.True or false: “typing a new spoken word” is the model. (a) True (b) False
  34. 34.⏩ In machine learning, which comes first: recorded spoken words or tomorrow’s rain guess? (a) recorded spoken words (b) tomorrow’s rain guess
  35. 35.True or false: “labelled fruit photos” is training data. (a) True (b) False
  36. 36.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) training data (c) a prediction
  37. 37.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  38. 38.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  39. 39.Which of these is the model? (a) past weather records (b) flagging a new email (c) tomorrow’s rain guess (d) the trained program
  40. 40.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) a prediction (c) the model

Answer key

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

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