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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 471 · 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.Which of these is training data? (a) the learned patterns (b) labelled fruit photos (c) tomorrow’s rain guess (d) naming a new fruit photo
  2. 2.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) training data (c) a password (d) a prediction
  3. 3.📦 What happens during training? (a) it charges up (b) it takes photos (c) it prints labels (d) it learns patterns
  4. 4.True or false: “past weather records” is training data. (a) False (b) True
  5. 5.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) training data (c) the model
  6. 6.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to change its name (d) to delete its data
  7. 7.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) the model (c) training data
  8. 8.Which of these is training data? (a) recorded spoken words (b) flagging a new email (c) typing a new spoken word (d) naming a new leaf
  9. 9.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
  10. 10.Which of these is training data? (a) naming a new leaf (b) old emails marked spam (c) typing a new spoken word (d) the trained program
  11. 11.⏩ In machine learning, which comes first: 500 labelled leaf photos or the trained program? (a) 500 labelled leaf photos (b) the trained program
  12. 12.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) a prediction (c) training data
  13. 13.True or false: “the learned patterns” is a prediction. (a) True (b) False
  14. 14.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) training data (c) a prediction
  15. 15.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  16. 16.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
  17. 17.Which of these is a prediction? (a) past weather records (b) labelled fruit photos (c) flagging a new email (d) 500 labelled leaf photos
  18. 18.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  19. 19.Which of these is the model? (a) typing a new spoken word (b) what training builds (c) 500 labelled leaf photos (d) old emails marked spam
  20. 20.Which of these is training data? (a) past weather records (b) the trained program (c) naming a new fruit photo (d) tomorrow’s rain guess
  21. 21.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  22. 22.True or false: “recorded spoken words” is training data. (a) True (b) False
  23. 23.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  24. 24.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, model, prediction (d) data, prediction, model
  25. 25.⏩ In machine learning, which comes first: labelled fruit photos or tomorrow’s rain guess? (a) labelled fruit photos (b) tomorrow’s rain guess
  26. 26.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  27. 27.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  28. 28.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  29. 29.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  30. 30.True or false: “naming a new fruit photo” is training data. (a) True (b) False
  31. 31.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  32. 32.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  33. 33.Which of these is a prediction? (a) recorded spoken words (b) past weather records (c) what training builds (d) tomorrow’s rain guess
  34. 34.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) the model (c) training data
  35. 35.⏩ In machine learning, which comes first: naming a new fruit photo or old emails marked spam? (a) naming a new fruit photo (b) old emails marked spam
  36. 36.⏩ 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
  37. 37.Which of these is the model? (a) labelled fruit photos (b) recorded spoken words (c) naming a new leaf (d) the trained program
  38. 38.⏩ In machine learning, which comes first: recorded spoken words or naming a new leaf? (a) recorded spoken words (b) naming a new leaf
  39. 39.⏩ 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
  40. 40.True or false: “500 labelled leaf photos” is training data. (a) False (b) True

Answer key

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

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