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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 694 · 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.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
  2. 2.Which of these is training data? (a) naming a new fruit photo (b) naming a new leaf (c) labelled fruit photos (d) what training builds
  3. 3.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
  4. 4.📦 What happens during training? (a) it takes photos (b) it learns patterns (c) it charges up (d) it prints labels
  5. 5.Which of these is a prediction? (a) labelled fruit photos (b) the trained program (c) 500 labelled leaf photos (d) naming a new leaf
  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.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  8. 8.True or false: “labelled fruit photos” is the model. (a) True (b) False
  9. 9.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to delete its data (d) to see if it works
  10. 10.Which of these is the model? (a) the trained program (b) typing a new spoken word (c) labelled fruit photos (d) recorded spoken words
  11. 11.⏩ In machine learning, which comes first: flagging a new email or past weather records? (a) flagging a new email (b) past weather records
  12. 12.⏩ In machine learning, which comes first: recorded spoken words or the learned patterns? (a) recorded spoken words (b) the learned patterns
  13. 13.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) training data (c) the model
  14. 14.Which of these is a prediction? (a) naming a new fruit photo (b) the trained program (c) 500 labelled leaf photos (d) old emails marked spam
  15. 15.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
  16. 16.Which of these is training data? (a) typing a new spoken word (b) the learned patterns (c) flagging a new email (d) 500 labelled leaf photos
  17. 17.⏩ In machine learning, which comes first: the trained program or labelled fruit photos? (a) the trained program (b) labelled fruit photos
  18. 18.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  19. 19.True or false: “old emails marked spam” is a prediction. (a) False (b) True
  20. 20.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  21. 21.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) the model (c) training data
  22. 22.True or false: “labelled fruit photos” is a prediction. (a) False (b) True
  23. 23.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) training data (c) a prediction
  24. 24.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  25. 25.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) training data (c) a prediction (d) a label error
  26. 26.True or false: “recorded spoken words” is the model. (a) True (b) False
  27. 27.Which of these is a prediction? (a) the learned patterns (b) past weather records (c) recorded spoken words (d) typing a new spoken word
  28. 28.Which of these is training data? (a) flagging a new email (b) the trained program (c) tomorrow’s rain guess (d) old emails marked spam
  29. 29.True or false: “typing a new spoken word” is the model. (a) False (b) True
  30. 30.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
  31. 31.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
  32. 32.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  33. 33.True or false: “what training builds” is the model. (a) False (b) True
  34. 34.⏩ 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
  35. 35.True or false: “labelled fruit photos” is training data. (a) False (b) True
  36. 36.⏩ In machine learning, which comes first: what training builds or past weather records? (a) what training builds (b) past weather records
  37. 37.Which of these is the model? (a) recorded spoken words (b) the learned patterns (c) naming a new leaf (d) 500 labelled leaf photos
  38. 38.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  39. 39.⏩ In machine learning, which comes first: the trained program or typing a new spoken word? (a) the trained program (b) typing a new spoken word
  40. 40.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction

Answer key

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

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