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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 631 · 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 learned patterns”? (a) training data (b) a prediction (c) the model
  2. 2.⏩ In machine learning, which comes first: labelled fruit photos or the learned patterns? (a) labelled fruit photos (b) the learned patterns
  3. 3.True or false: “labelled fruit photos” is the model. (a) True (b) False
  4. 4.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to see if it works (d) to delete its data
  5. 5.Which of these is the model? (a) 500 labelled leaf photos (b) the trained program (c) typing a new spoken word (d) labelled fruit photos
  6. 6.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) training data (c) a prediction
  7. 7.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False
  8. 8.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  9. 9.Which of these is a prediction? (a) flagging a new email (b) labelled fruit photos (c) what training builds (d) past weather records
  10. 10.True or false: “naming a new leaf” is a prediction. (a) False (b) True
  11. 11.🔁 What is the right order? (a) model, prediction, data (b) prediction, data, model (c) data, prediction, model (d) data, model, prediction
  12. 12.Which of these is the model? (a) typing a new spoken word (b) flagging a new email (c) the learned patterns (d) tomorrow’s rain guess
  13. 13.True or false: “naming a new fruit photo” is training data. (a) False (b) True
  14. 14.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  15. 15.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a password (c) training data (d) a prediction
  16. 16.True or false: “typing a new spoken word” is the model. (a) True (b) False
  17. 17.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
  18. 18.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  19. 19.True or false: “recorded spoken words” is training data. (a) False (b) True
  20. 20.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  21. 21.True or false: “labelled fruit photos” is a prediction. (a) False (b) True
  22. 22.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  23. 23.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  24. 24.True or false: “what training builds” is a prediction. (a) True (b) False
  25. 25.⏩ In machine learning, which comes first: old emails marked spam or naming a new leaf? (a) old emails marked spam (b) naming a new leaf
  26. 26.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it takes photos (d) it prints labels
  27. 27.⏩ In machine learning, which comes first: recorded spoken words or naming a new leaf? (a) recorded spoken words (b) naming a new leaf
  28. 28.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  29. 29.⏩ 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
  30. 30.Which of these is training data? (a) naming a new fruit photo (b) what training builds (c) the learned patterns (d) 500 labelled leaf photos
  31. 31.True or false: “past weather records” is training data. (a) True (b) False
  32. 32.Which of these is training data? (a) labelled fruit photos (b) the trained program (c) what training builds (d) typing a new spoken word
  33. 33.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  34. 34.⏩ In machine learning, which comes first: naming a new fruit photo or 500 labelled leaf photos? (a) naming a new fruit photo (b) 500 labelled leaf photos
  35. 35.True or false: “recorded spoken words” is a prediction. (a) False (b) True
  36. 36.Which of these is the model? (a) past weather records (b) naming a new leaf (c) tomorrow’s rain guess (d) what training builds
  37. 37.⏩ In machine learning, which comes first: the trained program or 500 labelled leaf photos? (a) the trained program (b) 500 labelled leaf photos
  38. 38.Which of these is a prediction? (a) labelled fruit photos (b) the learned patterns (c) tomorrow’s rain guess (d) the trained program
  39. 39.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) the model (c) a prediction
  40. 40.Which of these is a prediction? (a) 500 labelled leaf photos (b) past weather records (c) the trained program (d) naming a new fruit photo

Answer key

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

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