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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 668 · 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.📦 What happens during training? (a) it takes photos (b) it charges up (c) it learns patterns (d) it prints labels
  2. 2.Which of these is a prediction? (a) 500 labelled leaf photos (b) the learned patterns (c) naming a new fruit photo (d) what training builds
  3. 3.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  4. 4.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False
  5. 5.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a prediction (c) a label error (d) a password
  6. 6.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
  7. 7.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
  8. 8.Which of these is the model? (a) past weather records (b) what training builds (c) tomorrow’s rain guess (d) labelled fruit photos
  9. 9.Which of these is training data? (a) old emails marked spam (b) naming a new leaf (c) flagging a new email (d) the trained program
  10. 10.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  11. 11.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  12. 12.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
  13. 13.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  14. 14.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  15. 15.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  16. 16.Which of these is training data? (a) the trained program (b) typing a new spoken word (c) past weather records (d) naming a new leaf
  17. 17.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
  18. 18.⏩ In machine learning, which comes first: typing a new spoken word or the trained program? (a) typing a new spoken word (b) the trained program
  19. 19.⏩ In machine learning, which comes first: typing a new spoken word or labelled fruit photos? (a) typing a new spoken word (b) labelled fruit photos
  20. 20.⏩ 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
  21. 21.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  22. 22.Which of these is a prediction? (a) old emails marked spam (b) typing a new spoken word (c) the learned patterns (d) recorded spoken words
  23. 23.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program
  24. 24.⏩ In machine learning, which comes first: the trained program or past weather records? (a) the trained program (b) past weather records
  25. 25.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) data, model, prediction (d) model, prediction, data
  26. 26.⏩ In machine learning, which comes first: labelled fruit photos or the trained program? (a) labelled fruit photos (b) the trained program
  27. 27.True or false: “recorded spoken words” is training data. (a) True (b) False
  28. 28.Which of these is a prediction? (a) recorded spoken words (b) tomorrow’s rain guess (c) what training builds (d) past weather records
  29. 29.Which of these is training data? (a) naming a new fruit photo (b) the learned patterns (c) tomorrow’s rain guess (d) labelled fruit photos
  30. 30.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  31. 31.⏩ In machine learning, which comes first: 500 labelled leaf photos or the trained program? (a) 500 labelled leaf photos (b) the trained program
  32. 32.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  33. 33.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) the model (c) training data
  34. 34.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) a prediction (c) the model
  35. 35.True or false: “labelled fruit photos” is the model. (a) False (b) True
  36. 36.⏩ In machine learning, which comes first: typing a new spoken word or the learned patterns? (a) typing a new spoken word (b) the learned patterns
  37. 37.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  38. 38.🧪 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
  39. 39.Which of these is the model? (a) past weather records (b) tomorrow’s rain guess (c) typing a new spoken word (d) the trained program
  40. 40.True or false: “what training builds” is a prediction. (a) False (b) True

Answer key

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

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