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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 99 · 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 trained program or naming a new fruit photo? (a) the trained program (b) naming a new fruit photo
  2. 2.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to delete its data (d) to see if it works
  3. 3.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  4. 4.True or false: “old emails marked spam” is training data. (a) True (b) False
  5. 5.Which of these is training data? (a) the learned patterns (b) flagging a new email (c) naming a new leaf (d) recorded spoken words
  6. 6.⏩ In machine learning, which comes first: old emails marked spam or the learned patterns? (a) old emails marked spam (b) the learned patterns
  7. 7.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  8. 8.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a prediction (c) training data (d) a password
  9. 9.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) the model (c) training data
  10. 10.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  11. 11.True or false: “labelled fruit photos” is training data. (a) False (b) True
  12. 12.True or false: “typing a new spoken word” is the model. (a) True (b) False
  13. 13.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
  14. 14.Which of these is the model? (a) old emails marked spam (b) tomorrow’s rain guess (c) flagging a new email (d) what training builds
  15. 15.True or false: “the trained program” is a prediction. (a) True (b) False
  16. 16.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) prediction, data, model (d) data, model, prediction
  17. 17.⏩ In machine learning, which comes first: tomorrow’s rain guess or past weather records? (a) tomorrow’s rain guess (b) past weather records
  18. 18.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
  19. 19.Which of these is a prediction? (a) old emails marked spam (b) what training builds (c) the learned patterns (d) flagging a new email
  20. 20.Which of these is training data? (a) the learned patterns (b) typing a new spoken word (c) labelled fruit photos (d) naming a new leaf
  21. 21.True or false: “recorded spoken words” is training data. (a) True (b) False
  22. 22.True or false: “naming a new fruit photo” is training data. (a) False (b) True
  23. 23.True or false: “the trained program” is the model. (a) True (b) False
  24. 24.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  25. 25.Which of these is training data? (a) the learned patterns (b) flagging a new email (c) old emails marked spam (d) tomorrow’s rain guess
  26. 26.📦 What happens during training? (a) it learns patterns (b) it prints labels (c) it charges up (d) it takes photos
  27. 27.Which of these is a prediction? (a) past weather records (b) what training builds (c) naming a new fruit photo (d) labelled fruit photos
  28. 28.Which of these is the model? (a) typing a new spoken word (b) tomorrow’s rain guess (c) the learned patterns (d) naming a new fruit photo
  29. 29.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
  30. 30.Which of these is training data? (a) the learned patterns (b) what training builds (c) past weather records (d) the trained program
  31. 31.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  32. 32.⏩ In machine learning, which comes first: the trained program or past weather records? (a) the trained program (b) past weather records
  33. 33.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  34. 34.True or false: “naming a new fruit photo” is the model. (a) True (b) False
  35. 35.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  36. 36.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  37. 37.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  38. 38.True or false: “typing a new spoken word” is training data. (a) True (b) False
  39. 39.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model
  40. 40.⏩ In machine learning, which comes first: the learned patterns or labelled fruit photos? (a) the learned patterns (b) labelled fruit photos

Answer key

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

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