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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 866 · 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) recorded spoken words (b) naming a new fruit photo (c) the trained program (d) naming a new leaf
  2. 2.Which of these is the model? (a) what training builds (b) recorded spoken words (c) tomorrow’s rain guess (d) naming a new leaf
  3. 3.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) model, prediction, data (d) data, prediction, model
  4. 4.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  5. 5.🔁 Training data, the model or a prediction: “old emails marked spam”? (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 change its name (c) to delete its data (d) to see if it works
  7. 7.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) a prediction (c) the model
  8. 8.Which of these is a prediction? (a) what training builds (b) old emails marked spam (c) labelled fruit photos (d) flagging a new email
  9. 9.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
  10. 10.📦 What happens during training? (a) it takes photos (b) it charges up (c) it prints labels (d) it learns patterns
  11. 11.True or false: “past weather records” is the model. (a) True (b) False
  12. 12.True or false: “the learned patterns” is the model. (a) True (b) False
  13. 13.True or false: “labelled fruit photos” is training data. (a) False (b) True
  14. 14.True or false: “typing a new spoken word” is the model. (a) True (b) False
  15. 15.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
  16. 16.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  17. 17.Which of these is training data? (a) labelled fruit photos (b) flagging a new email (c) the learned patterns (d) naming a new fruit photo
  18. 18.True or false: “naming a new leaf” is a prediction. (a) False (b) True
  19. 19.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) training data (c) a prediction
  20. 20.⏩ In machine learning, which comes first: typing a new spoken word or 500 labelled leaf photos? (a) typing a new spoken word (b) 500 labelled leaf photos
  21. 21.⏩ In machine learning, which comes first: old emails marked spam or the learned patterns? (a) old emails marked spam (b) the learned patterns
  22. 22.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  23. 23.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  24. 24.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a label error (c) a password (d) training data
  25. 25.True or false: “what training builds” is the model. (a) True (b) False
  26. 26.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) the model (c) training data
  27. 27.Which of these is the model? (a) tomorrow’s rain guess (b) naming a new fruit photo (c) typing a new spoken word (d) the trained program
  28. 28.⏩ 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
  29. 29.True or false: “what training builds” is training data. (a) False (b) True
  30. 30.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
  31. 31.Which of these is a prediction? (a) old emails marked spam (b) recorded spoken words (c) tomorrow’s rain guess (d) the trained program
  32. 32.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  33. 33.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  34. 34.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  35. 35.True or false: “old emails marked spam” is training data. (a) True (b) False
  36. 36.Which of these is a prediction? (a) old emails marked spam (b) recorded spoken words (c) naming a new leaf (d) past weather records
  37. 37.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program
  38. 38.Which of these is training data? (a) flagging a new email (b) past weather records (c) naming a new leaf (d) what training builds
  39. 39.⏩ In machine learning, which comes first: naming a new fruit photo or what training builds? (a) naming a new fruit photo (b) what training builds
  40. 40.⏩ In machine learning, which comes first: past weather records or naming a new leaf? (a) past weather records (b) naming a new leaf

Answer key

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

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