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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 197 · 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: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  2. 2.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  3. 3.⏩ In machine learning, which comes first: past weather records or naming a new leaf? (a) past weather records (b) naming a new leaf
  4. 4.Which of these is training data? (a) tomorrow’s rain guess (b) 500 labelled leaf photos (c) flagging a new email (d) what training builds
  5. 5.True or false: “typing a new spoken word” is the model. (a) False (b) True
  6. 6.True or false: “old emails marked spam” is a prediction. (a) True (b) False
  7. 7.True or false: “what training builds” is the model. (a) True (b) False
  8. 8.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False
  9. 9.⏩ 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
  10. 10.Which of these is a prediction? (a) the trained program (b) past weather records (c) naming a new fruit photo (d) recorded spoken words
  11. 11.True or false: “the trained program” is the model. (a) True (b) False
  12. 12.📦 What happens during training? (a) it learns patterns (b) it prints labels (c) it charges up (d) it takes photos
  13. 13.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
  14. 14.Which of these is the model? (a) what training builds (b) old emails marked spam (c) labelled fruit photos (d) 500 labelled leaf photos
  15. 15.Which of these is training data? (a) the learned patterns (b) typing a new spoken word (c) recorded spoken words (d) tomorrow’s rain guess
  16. 16.⏩ In machine learning, which comes first: flagging a new email or 500 labelled leaf photos? (a) flagging a new email (b) 500 labelled leaf photos
  17. 17.⏩ In machine learning, which comes first: naming a new leaf or labelled fruit photos? (a) naming a new leaf (b) labelled fruit photos
  18. 18.Which of these is the model? (a) naming a new fruit photo (b) typing a new spoken word (c) flagging a new email (d) the learned patterns
  19. 19.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  20. 20.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) training data (c) the model
  21. 21.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  22. 22.Which of these is a prediction? (a) past weather records (b) old emails marked spam (c) naming a new leaf (d) recorded spoken words
  23. 23.🧪 Why test a model on NEW examples? (a) to see if it works (b) to delete its data (c) to change its name (d) to make it slower
  24. 24.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  25. 25.⏩ In machine learning, which comes first: naming a new fruit photo or recorded spoken words? (a) naming a new fruit photo (b) recorded spoken words
  26. 26.True or false: “past weather records” is a prediction. (a) True (b) False
  27. 27.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  28. 28.True or false: “labelled fruit photos” is the model. (a) False (b) True
  29. 29.🔮 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
  30. 30.Which of these is the model? (a) 500 labelled leaf photos (b) naming a new fruit photo (c) tomorrow’s rain guess (d) the trained program
  31. 31.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  32. 32.True or false: “labelled fruit photos” is training data. (a) False (b) True
  33. 33.Which of these is a prediction? (a) old emails marked spam (b) past weather records (c) typing a new spoken word (d) recorded spoken words
  34. 34.True or false: “flagging a new email” is a prediction. (a) True (b) False
  35. 35.⏩ In machine learning, which comes first: flagging a new email or recorded spoken words? (a) flagging a new email (b) recorded spoken words
  36. 36.⏩ In machine learning, which comes first: the trained program or flagging a new email? (a) the trained program (b) flagging a new email
  37. 37.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) a prediction (c) the model
  38. 38.🔁 What is the right order? (a) data, prediction, model (b) data, model, prediction (c) model, prediction, data (d) prediction, data, model
  39. 39.True or false: “the trained program” is a prediction. (a) False (b) True
  40. 40.True or false: “what training builds” is training data. (a) False (b) True

Answer key

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

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