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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 603 · 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) 500 labelled leaf photos (b) naming a new fruit photo (c) recorded spoken words (d) old emails marked spam
  2. 2.⏩ In machine learning, which comes first: naming a new leaf or labelled fruit photos? (a) naming a new leaf (b) labelled fruit photos
  3. 3.⏩ In machine learning, which comes first: typing a new spoken word or the trained program? (a) typing a new spoken word (b) the trained program
  4. 4.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) training data (c) the model
  5. 5.True or false: “the learned patterns” is the model. (a) False (b) True
  6. 6.Which of these is a prediction? (a) old emails marked spam (b) what training builds (c) labelled fruit photos (d) tomorrow’s rain guess
  7. 7.🔁 What is the right order? (a) prediction, data, model (b) data, model, prediction (c) data, prediction, model (d) model, prediction, data
  8. 8.True or false: “recorded spoken words” is training data. (a) False (b) True
  9. 9.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  10. 10.True or false: “naming a new fruit photo” is the model. (a) False (b) True
  11. 11.Which of these is training data? (a) naming a new fruit photo (b) the learned patterns (c) recorded spoken words (d) tomorrow’s rain guess
  12. 12.True or false: “tomorrow’s rain guess” is training data. (a) False (b) True
  13. 13.Which of these is the model? (a) 500 labelled leaf photos (b) the learned patterns (c) tomorrow’s rain guess (d) old emails marked spam
  14. 14.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
  15. 15.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  16. 16.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) the model (c) training data
  17. 17.🧪 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
  18. 18.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  19. 19.True or false: “old emails marked spam” is training data. (a) True (b) False
  20. 20.Which of these is a prediction? (a) past weather records (b) flagging a new email (c) old emails marked spam (d) labelled fruit photos
  21. 21.⏩ In machine learning, which comes first: the learned patterns or labelled fruit photos? (a) the learned patterns (b) labelled fruit photos
  22. 22.⏩ 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
  23. 23.Which of these is training data? (a) flagging a new email (b) the learned patterns (c) labelled fruit photos (d) naming a new fruit photo
  24. 24.True or false: “flagging a new email” is a prediction. (a) True (b) False
  25. 25.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  26. 26.True or false: “what training builds” is a prediction. (a) True (b) False
  27. 27.Which of these is training data? (a) the learned patterns (b) old emails marked spam (c) flagging a new email (d) naming a new leaf
  28. 28.Which of these is training data? (a) past weather records (b) the learned patterns (c) the trained program (d) naming a new fruit photo
  29. 29.True or false: “naming a new leaf” is the model. (a) True (b) False
  30. 30.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  31. 31.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  32. 32.True or false: “past weather records” is training data. (a) True (b) False
  33. 33.📦 What happens during training? (a) it takes photos (b) it charges up (c) it learns patterns (d) it prints labels
  34. 34.⏩ In machine learning, which comes first: the learned patterns or old emails marked spam? (a) the learned patterns (b) old emails marked spam
  35. 35.True or false: “old emails marked spam” is a prediction. (a) True (b) False
  36. 36.⏩ In machine learning, which comes first: what training builds or 500 labelled leaf photos? (a) what training builds (b) 500 labelled leaf photos
  37. 37.🔮 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
  38. 38.Which of these is the model? (a) recorded spoken words (b) old emails marked spam (c) flagging a new email (d) what training builds
  39. 39.Which of these is a prediction? (a) past weather records (b) 500 labelled leaf photos (c) naming a new leaf (d) recorded spoken words
  40. 40.True or false: “typing a new spoken word” is training data. (a) True (b) False

Answer key

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

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