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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 225 · 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 prints labels (c) it charges up (d) it learns patterns
  2. 2.Which of these is a prediction? (a) what training builds (b) naming a new fruit photo (c) past weather records (d) the trained program
  3. 3.Which of these is training data? (a) what training builds (b) flagging a new email (c) naming a new leaf (d) old emails marked spam
  4. 4.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
  5. 5.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
  6. 6.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) training data (c) a prediction
  7. 7.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  8. 8.True or false: “the trained program” is the model. (a) True (b) False
  9. 9.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) model, prediction, data (d) data, prediction, model
  10. 10.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  11. 11.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) training data (c) the model
  12. 12.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  13. 13.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  14. 14.⏩ 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
  15. 15.⏩ In machine learning, which comes first: naming a new leaf or recorded spoken words? (a) naming a new leaf (b) recorded spoken words
  16. 16.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a prediction (c) a label error (d) training data
  17. 17.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  18. 18.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
  19. 19.🧪 Why test a model on NEW examples? (a) to see if it works (b) to make it slower (c) to change its name (d) to delete its data
  20. 20.Which of these is training data? (a) the learned patterns (b) tomorrow’s rain guess (c) labelled fruit photos (d) the trained program
  21. 21.Which of these is training data? (a) naming a new leaf (b) the trained program (c) 500 labelled leaf photos (d) the learned patterns
  22. 22.Which of these is the model? (a) 500 labelled leaf photos (b) the trained program (c) naming a new fruit photo (d) tomorrow’s rain guess
  23. 23.True or false: “tomorrow’s rain guess” is training data. (a) True (b) False
  24. 24.True or false: “recorded spoken words” is training data. (a) False (b) True
  25. 25.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  26. 26.Which of these is training data? (a) naming a new fruit photo (b) recorded spoken words (c) what training builds (d) the learned patterns
  27. 27.True or false: “past weather records” is a prediction. (a) True (b) False
  28. 28.⏩ In machine learning, which comes first: old emails marked spam or typing a new spoken word? (a) old emails marked spam (b) typing a new spoken word
  29. 29.Which of these is the model? (a) naming a new leaf (b) 500 labelled leaf photos (c) naming a new fruit photo (d) what training builds
  30. 30.⏩ In machine learning, which comes first: the trained program or recorded spoken words? (a) the trained program (b) recorded spoken words
  31. 31.True or false: “old emails marked spam” is the model. (a) False (b) True
  32. 32.⏩ In machine learning, which comes first: old emails marked spam or the learned patterns? (a) old emails marked spam (b) the learned patterns
  33. 33.True or false: “past weather records” is the model. (a) True (b) False
  34. 34.True or false: “naming a new leaf” is a prediction. (a) False (b) True
  35. 35.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  36. 36.⏩ In machine learning, which comes first: what training builds or labelled fruit photos? (a) what training builds (b) labelled fruit photos
  37. 37.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  38. 38.Which of these is a prediction? (a) the learned patterns (b) labelled fruit photos (c) what training builds (d) naming a new leaf
  39. 39.True or false: “old emails marked spam” is a prediction. (a) False (b) True
  40. 40.True or false: “the learned patterns” is training data. (a) False (b) True

Answer key

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

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