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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 250 · 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 a prediction? (a) old emails marked spam (b) the trained program (c) the learned patterns (d) typing a new spoken word
  2. 2.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to change its name (d) to delete its data
  3. 3.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a label error (c) training data (d) a prediction
  4. 4.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  5. 5.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
  6. 6.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  7. 7.True or false: “labelled fruit photos” is training data. (a) True (b) False
  8. 8.True or false: “the trained program” is a prediction. (a) True (b) False
  9. 9.Which of these is training data? (a) the learned patterns (b) typing a new spoken word (c) naming a new fruit photo (d) labelled fruit photos
  10. 10.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  11. 11.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  12. 12.True or false: “naming a new leaf” is a prediction. (a) True (b) False
  13. 13.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  14. 14.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  15. 15.Which of these is training data? (a) flagging a new email (b) naming a new leaf (c) 500 labelled leaf photos (d) the trained program
  16. 16.⏩ In machine learning, which comes first: what training builds or old emails marked spam? (a) what training builds (b) old emails marked spam
  17. 17.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  18. 18.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it prints labels (d) it takes photos
  19. 19.Which of these is a prediction? (a) the learned patterns (b) recorded spoken words (c) naming a new fruit photo (d) labelled fruit photos
  20. 20.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  21. 21.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  22. 22.Which of these is a prediction? (a) past weather records (b) recorded spoken words (c) flagging a new email (d) old emails marked spam
  23. 23.Which of these is training data? (a) naming a new fruit photo (b) what training builds (c) the learned patterns (d) recorded spoken words
  24. 24.True or false: “what training builds” is a prediction. (a) True (b) False
  25. 25.True or false: “the learned patterns” is a prediction. (a) False (b) True
  26. 26.⏩ In machine learning, which comes first: past weather records or naming a new fruit photo? (a) past weather records (b) naming a new fruit photo
  27. 27.Which of these is the model? (a) naming a new fruit photo (b) the learned patterns (c) 500 labelled leaf photos (d) naming a new leaf
  28. 28.⏩ In machine learning, which comes first: past weather records or typing a new spoken word? (a) past weather records (b) typing a new spoken word
  29. 29.True or false: “old emails marked spam” is training data. (a) True (b) False
  30. 30.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  31. 31.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  32. 32.⏩ In machine learning, which comes first: the learned patterns or naming a new fruit photo? (a) the learned patterns (b) naming a new fruit photo
  33. 33.⏩ 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
  34. 34.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  35. 35.True or false: “old emails marked spam” is the model. (a) False (b) True
  36. 36.True or false: “past weather records” is training data. (a) True (b) False
  37. 37.⏩ In machine learning, which comes first: the trained program or typing a new spoken word? (a) the trained program (b) typing a new spoken word
  38. 38.Which of these is training data? (a) typing a new spoken word (b) the trained program (c) naming a new leaf (d) old emails marked spam
  39. 39.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
  40. 40.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns

Answer key

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

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