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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 845 · 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: “the learned patterns”? (a) the model (b) a prediction (c) training data
  2. 2.⏩ 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
  3. 3.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
  4. 4.True or false: “old emails marked spam” is the model. (a) True (b) False
  5. 5.True or false: “the trained program” is training data. (a) False (b) True
  6. 6.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to change its name (d) to see if it works
  7. 7.Which of these is the model? (a) what training builds (b) tomorrow’s rain guess (c) naming a new leaf (d) 500 labelled leaf photos
  8. 8.True or false: “recorded spoken words” is the model. (a) False (b) True
  9. 9.⏩ In machine learning, which comes first: recorded spoken words or what training builds? (a) recorded spoken words (b) what training builds
  10. 10.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
  11. 11.True or false: “labelled fruit photos” is training data. (a) False (b) True
  12. 12.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  13. 13.Which of these is a prediction? (a) 500 labelled leaf photos (b) flagging a new email (c) what training builds (d) the trained program
  14. 14.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  15. 15.⏩ 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
  16. 16.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
  17. 17.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  18. 18.Which of these is a prediction? (a) 500 labelled leaf photos (b) typing a new spoken word (c) what training builds (d) the trained program
  19. 19.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  20. 20.True or false: “the trained program” is the model. (a) True (b) False
  21. 21.⏩ In machine learning, which comes first: the learned patterns or recorded spoken words? (a) the learned patterns (b) recorded spoken words
  22. 22.⏩ 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
  23. 23.True or false: “the learned patterns” is training data. (a) False (b) True
  24. 24.Which of these is training data? (a) flagging a new email (b) the learned patterns (c) typing a new spoken word (d) labelled fruit photos
  25. 25.True or false: “what training builds” is training data. (a) False (b) True
  26. 26.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) the model (c) a prediction
  27. 27.Which of these is a prediction? (a) the trained program (b) old emails marked spam (c) 500 labelled leaf photos (d) naming a new leaf
  28. 28.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model
  29. 29.⏩ In machine learning, which comes first: what training builds or past weather records? (a) what training builds (b) past weather records
  30. 30.True or false: “naming a new fruit photo” is a prediction. (a) False (b) True
  31. 31.Which of these is the model? (a) recorded spoken words (b) 500 labelled leaf photos (c) flagging a new email (d) the learned patterns
  32. 32.Which of these is a prediction? (a) what training builds (b) naming a new fruit photo (c) recorded spoken words (d) labelled fruit photos
  33. 33.⏩ In machine learning, which comes first: what training builds or labelled fruit photos? (a) what training builds (b) labelled fruit photos
  34. 34.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program
  35. 35.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) data, model, prediction (d) prediction, data, model
  36. 36.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  37. 37.True or false: “past weather records” is training data. (a) False (b) True
  38. 38.⏩ 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
  39. 39.Which of these is a prediction? (a) 500 labelled leaf photos (b) tomorrow’s rain guess (c) labelled fruit photos (d) old emails marked spam
  40. 40.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records

Answer key

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

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