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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 91 · 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: what training builds or 500 labelled leaf photos? (a) what training builds (b) 500 labelled leaf photos
  2. 2.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction
  3. 3.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  4. 4.Which of these is a prediction? (a) what training builds (b) recorded spoken words (c) flagging a new email (d) the learned patterns
  5. 5.Which of these is a prediction? (a) tomorrow’s rain guess (b) recorded spoken words (c) what training builds (d) the learned patterns
  6. 6.True or false: “past weather records” is a prediction. (a) False (b) True
  7. 7.Which of these is a prediction? (a) the trained program (b) past weather records (c) the learned patterns (d) typing a new spoken word
  8. 8.🔁 What is the right order? (a) model, prediction, data (b) prediction, data, model (c) data, model, prediction (d) data, prediction, model
  9. 9.True or false: “past weather records” is training data. (a) False (b) True
  10. 10.🧪 Why test a model on NEW examples? (a) to delete its data (b) to change its name (c) to see if it works (d) to make it slower
  11. 11.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  12. 12.True or false: “the trained program” is a prediction. (a) False (b) True
  13. 13.Which of these is the model? (a) the learned patterns (b) past weather records (c) tomorrow’s rain guess (d) flagging a new email
  14. 14.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  15. 15.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  16. 16.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  17. 17.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
  18. 18.Which of these is training data? (a) flagging a new email (b) what training builds (c) old emails marked spam (d) the trained program
  19. 19.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  20. 20.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  21. 21.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  22. 22.Which of these is the model? (a) 500 labelled leaf photos (b) typing a new spoken word (c) what training builds (d) past weather records
  23. 23.True or false: “500 labelled leaf photos” is the model. (a) True (b) False
  24. 24.🔮 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
  25. 25.Which of these is training data? (a) labelled fruit photos (b) the learned patterns (c) flagging a new email (d) tomorrow’s rain guess
  26. 26.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  27. 27.True or false: “recorded spoken words” is a prediction. (a) True (b) False
  28. 28.⏩ In machine learning, which comes first: naming a new fruit photo or the learned patterns? (a) naming a new fruit photo (b) the learned patterns
  29. 29.True or false: “the learned patterns” is training data. (a) True (b) False
  30. 30.True or false: “typing a new spoken word” is training data. (a) False (b) True
  31. 31.Which of these is the model? (a) naming a new fruit photo (b) labelled fruit photos (c) the trained program (d) tomorrow’s rain guess
  32. 32.Which of these is training data? (a) tomorrow’s rain guess (b) 500 labelled leaf photos (c) naming a new fruit photo (d) naming a new leaf
  33. 33.True or false: “the learned patterns” is the model. (a) False (b) True
  34. 34.⏩ In machine learning, which comes first: labelled fruit photos or flagging a new email? (a) labelled fruit photos (b) flagging a new email
  35. 35.Which of these is training data? (a) the learned patterns (b) tomorrow’s rain guess (c) past weather records (d) naming a new leaf
  36. 36.True or false: “recorded spoken words” is the model. (a) True (b) False
  37. 37.Which of these is training data? (a) recorded spoken words (b) the trained program (c) the learned patterns (d) flagging a new email
  38. 38.⏩ In machine learning, which comes first: old emails marked spam or typing a new spoken word? (a) old emails marked spam (b) typing a new spoken word
  39. 39.True or false: “naming a new leaf” is training data. (a) True (b) False
  40. 40.Which of these is a prediction? (a) what training builds (b) labelled fruit photos (c) naming a new fruit photo (d) 500 labelled leaf photos

Answer key

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

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