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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 639 · 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: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  2. 2.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  3. 3.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  4. 4.Which of these is the model? (a) labelled fruit photos (b) tomorrow’s rain guess (c) the trained program (d) old emails marked spam
  5. 5.Which of these is a prediction? (a) what training builds (b) old emails marked spam (c) the learned patterns (d) tomorrow’s rain guess
  6. 6.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  7. 7.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  8. 8.Which of these is a prediction? (a) the learned patterns (b) the trained program (c) flagging a new email (d) old emails marked spam
  9. 9.True or false: “old emails marked spam” is the model. (a) True (b) False
  10. 10.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
  11. 11.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  12. 12.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  13. 13.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
  14. 14.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a label error (c) a prediction (d) a password
  15. 15.⏩ 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
  16. 16.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  17. 17.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
  18. 18.True or false: “typing a new spoken word” is training data. (a) True (b) False
  19. 19.📦 What happens during training? (a) it takes photos (b) it charges up (c) it prints labels (d) it learns patterns
  20. 20.⏩ In machine learning, which comes first: recorded spoken words or the learned patterns? (a) recorded spoken words (b) the learned patterns
  21. 21.⏩ In machine learning, which comes first: labelled fruit photos or the learned patterns? (a) labelled fruit photos (b) the learned patterns
  22. 22.True or false: “the trained program” is training data. (a) False (b) True
  23. 23.⏩ In machine learning, which comes first: what training builds or 500 labelled leaf photos? (a) what training builds (b) 500 labelled leaf photos
  24. 24.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
  25. 25.⏩ 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
  26. 26.Which of these is a prediction? (a) labelled fruit photos (b) typing a new spoken word (c) old emails marked spam (d) what training builds
  27. 27.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  28. 28.⏩ In machine learning, which comes first: recorded spoken words or the trained program? (a) recorded spoken words (b) the trained program
  29. 29.Which of these is a prediction? (a) naming a new fruit photo (b) labelled fruit photos (c) old emails marked spam (d) what training builds
  30. 30.True or false: “the learned patterns” is the model. (a) True (b) False
  31. 31.True or false: “naming a new leaf” is the model. (a) False (b) True
  32. 32.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  33. 33.Which of these is a prediction? (a) the learned patterns (b) recorded spoken words (c) naming a new leaf (d) 500 labelled leaf photos
  34. 34.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
  35. 35.True or false: “tomorrow’s rain guess” is training data. (a) False (b) True
  36. 36.True or false: “naming a new leaf” is a prediction. (a) False (b) True
  37. 37.🧪 Why test a model on NEW examples? (a) to delete its data (b) to see if it works (c) to change its name (d) to make it slower
  38. 38.True or false: “flagging a new email” is training data. (a) False (b) True
  39. 39.True or false: “the learned patterns” is a prediction. (a) False (b) True
  40. 40.Which of these is training data? (a) labelled fruit photos (b) the trained program (c) naming a new leaf (d) the learned patterns

Answer key

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

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