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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 826 · 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.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
  2. 2.True or false: “recorded spoken words” is training data. (a) True (b) False
  3. 3.Which of these is the model? (a) the learned patterns (b) labelled fruit photos (c) flagging a new email (d) 500 labelled leaf photos
  4. 4.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  5. 5.Which of these is a prediction? (a) the trained program (b) recorded spoken words (c) naming a new leaf (d) labelled fruit photos
  6. 6.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
  7. 7.Which of these is training data? (a) flagging a new email (b) the trained program (c) labelled fruit photos (d) tomorrow’s rain guess
  8. 8.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  9. 9.⏩ In machine learning, which comes first: the trained program or 500 labelled leaf photos? (a) the trained program (b) 500 labelled leaf photos
  10. 10.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a password (c) a prediction (d) a label error
  11. 11.Which of these is training data? (a) typing a new spoken word (b) the trained program (c) past weather records (d) the learned patterns
  12. 12.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
  13. 13.⏩ 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
  14. 14.Which of these is the model? (a) naming a new leaf (b) past weather records (c) flagging a new email (d) the trained program
  15. 15.True or false: “the learned patterns” is the model. (a) False (b) True
  16. 16.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) the model (c) training data
  17. 17.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  18. 18.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  19. 19.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  20. 20.⏩ In machine learning, which comes first: recorded spoken words or the trained program? (a) recorded spoken words (b) the trained program
  21. 21.True or false: “typing a new spoken word” is training data. (a) True (b) False
  22. 22.True or false: “the trained program” is the model. (a) False (b) True
  23. 23.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
  24. 24.True or false: “flagging a new email” is a prediction. (a) True (b) False
  25. 25.True or false: “tomorrow’s rain guess” is training data. (a) False (b) True
  26. 26.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  27. 27.Which of these is the model? (a) flagging a new email (b) typing a new spoken word (c) 500 labelled leaf photos (d) what training builds
  28. 28.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  29. 29.📦 What happens during training? (a) it prints labels (b) it learns patterns (c) it takes photos (d) it charges up
  30. 30.True or false: “typing a new spoken word” is the model. (a) True (b) False
  31. 31.Which of these is a prediction? (a) the trained program (b) recorded spoken words (c) tomorrow’s rain guess (d) labelled fruit photos
  32. 32.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  33. 33.🔁 What is the right order? (a) model, prediction, data (b) data, prediction, model (c) prediction, data, model (d) data, model, prediction
  34. 34.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess
  35. 35.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
  36. 36.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to delete its data (d) to change its name
  37. 37.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  38. 38.Which of these is training data? (a) 500 labelled leaf photos (b) naming a new fruit photo (c) naming a new leaf (d) what training builds
  39. 39.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  40. 40.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False

Answer key

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

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