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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 782 · 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.⏩ In machine learning, which comes first: the learned patterns or labelled fruit photos? (a) the learned patterns (b) labelled fruit photos
  2. 2.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) the model (c) a prediction
  3. 3.Which of these is training data? (a) tomorrow’s rain guess (b) recorded spoken words (c) flagging a new email (d) naming a new fruit photo
  4. 4.Which of these is training data? (a) what training builds (b) typing a new spoken word (c) 500 labelled leaf photos (d) the trained program
  5. 5.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to make it slower (d) to see if it works
  6. 6.⏩ 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
  7. 7.⏩ In machine learning, which comes first: what training builds or 500 labelled leaf photos? (a) what training builds (b) 500 labelled leaf photos
  8. 8.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  9. 9.📦 What happens during training? (a) it charges up (b) it takes photos (c) it prints labels (d) it learns patterns
  10. 10.True or false: “the learned patterns” is training data. (a) True (b) False
  11. 11.Which of these is a prediction? (a) 500 labelled leaf photos (b) what training builds (c) past weather records (d) typing a new spoken word
  12. 12.True or false: “past weather records” is a prediction. (a) True (b) False
  13. 13.True or false: “recorded spoken words” is the model. (a) True (b) False
  14. 14.True or false: “the learned patterns” is the model. (a) False (b) True
  15. 15.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
  16. 16.⏩ In machine learning, which comes first: labelled fruit photos or the trained program? (a) labelled fruit photos (b) the trained program
  17. 17.⏩ In machine learning, which comes first: what training builds or naming a new fruit photo? (a) what training builds (b) naming a new fruit photo
  18. 18.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  19. 19.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
  20. 20.Which of these is the model? (a) old emails marked spam (b) the learned patterns (c) naming a new fruit photo (d) past weather records
  21. 21.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  22. 22.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) a prediction (c) the model
  23. 23.True or false: “naming a new leaf” is a prediction. (a) False (b) True
  24. 24.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  25. 25.True or false: “naming a new fruit photo” is the model. (a) True (b) False
  26. 26.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  27. 27.🔁 What is the right order? (a) model, prediction, data (b) prediction, data, model (c) data, prediction, model (d) data, model, prediction
  28. 28.⏩ In machine learning, which comes first: typing a new spoken word or recorded spoken words? (a) typing a new spoken word (b) recorded spoken words
  29. 29.Which of these is a prediction? (a) naming a new leaf (b) what training builds (c) old emails marked spam (d) labelled fruit photos
  30. 30.⏩ In machine learning, which comes first: tomorrow’s rain guess or recorded spoken words? (a) tomorrow’s rain guess (b) recorded spoken words
  31. 31.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  32. 32.True or false: “what training builds” is training data. (a) True (b) False
  33. 33.Which of these is a prediction? (a) what training builds (b) 500 labelled leaf photos (c) old emails marked spam (d) naming a new fruit photo
  34. 34.Which of these is the model? (a) the trained program (b) labelled fruit photos (c) 500 labelled leaf photos (d) naming a new leaf
  35. 35.Which of these is a prediction? (a) what training builds (b) tomorrow’s rain guess (c) the learned patterns (d) labelled fruit photos
  36. 36.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess
  37. 37.True or false: “flagging a new email” is a prediction. (a) False (b) True
  38. 38.⏩ In machine learning, which comes first: naming a new fruit photo or the trained program? (a) naming a new fruit photo (b) the trained program
  39. 39.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
  40. 40.True or false: “tomorrow’s rain guess” is training data. (a) True (b) False

Answer key

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

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