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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 280 · 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: “labelled fruit photos” is training data. (a) True (b) False
  2. 2.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) training data (c) a label error (d) a password
  3. 3.🔁 What is the right order? (a) data, prediction, model (b) prediction, data, model (c) model, prediction, data (d) data, model, prediction
  4. 4.Which of these is the model? (a) the learned patterns (b) typing a new spoken word (c) recorded spoken words (d) naming a new fruit photo
  5. 5.True or false: “500 labelled leaf photos” is the model. (a) True (b) False
  6. 6.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) a prediction (c) the model
  7. 7.📦 What happens during training? (a) it prints labels (b) it takes photos (c) it learns patterns (d) it charges up
  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) past weather records (b) naming a new leaf (c) 500 labelled leaf photos (d) the learned patterns
  10. 10.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) a prediction (c) the model
  11. 11.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  12. 12.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  13. 13.Which of these is training data? (a) what training builds (b) flagging a new email (c) naming a new leaf (d) 500 labelled leaf photos
  14. 14.Which of these is training data? (a) flagging a new email (b) the learned patterns (c) what training builds (d) old emails marked spam
  15. 15.🧪 Why test a model on NEW examples? (a) to see if it works (b) to change its name (c) to make it slower (d) to delete its data
  16. 16.Which of these is training data? (a) the trained program (b) flagging a new email (c) past weather records (d) tomorrow’s rain guess
  17. 17.True or false: “flagging a new email” is training data. (a) True (b) False
  18. 18.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
  19. 19.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
  20. 20.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  21. 21.True or false: “naming a new leaf” is training data. (a) False (b) True
  22. 22.True or false: “past weather records” is the model. (a) False (b) True
  23. 23.True or false: “recorded spoken words” is the model. (a) True (b) False
  24. 24.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  25. 25.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) the model (c) training data
  26. 26.Which of these is the model? (a) past weather records (b) the trained program (c) tomorrow’s rain guess (d) naming a new fruit photo
  27. 27.Which of these is a prediction? (a) typing a new spoken word (b) labelled fruit photos (c) the trained program (d) past weather records
  28. 28.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  29. 29.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  30. 30.True or false: “past weather records” is training data. (a) False (b) True
  31. 31.Which of these is training data? (a) the learned patterns (b) labelled fruit photos (c) what training builds (d) typing a new spoken word
  32. 32.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  33. 33.True or false: “the trained program” is the model. (a) False (b) True
  34. 34.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  35. 35.⏩ In machine learning, which comes first: labelled fruit photos or naming a new leaf? (a) labelled fruit photos (b) naming a new leaf
  36. 36.True or false: “old emails marked spam” is a prediction. (a) False (b) True
  37. 37.Which of these is the model? (a) labelled fruit photos (b) what training builds (c) naming a new leaf (d) typing a new spoken word
  38. 38.⏩ 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
  39. 39.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
  40. 40.⏩ In machine learning, which comes first: recorded spoken words or tomorrow’s rain guess? (a) recorded spoken words (b) tomorrow’s rain guess

Answer key

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

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