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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 944 · 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 training data? (a) the learned patterns (b) what training builds (c) labelled fruit photos (d) tomorrow’s rain guess
  2. 2.🧪 Why test a model on NEW examples? (a) to change its name (b) to see if it works (c) to make it slower (d) to delete its data
  3. 3.Which of these is training data? (a) recorded spoken words (b) typing a new spoken word (c) the trained program (d) naming a new fruit photo
  4. 4.True or false: “recorded spoken words” is training data. (a) False (b) True
  5. 5.Which of these is a prediction? (a) recorded spoken words (b) typing a new spoken word (c) old emails marked spam (d) 500 labelled leaf photos
  6. 6.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  7. 7.Which of these is the model? (a) old emails marked spam (b) recorded spoken words (c) typing a new spoken word (d) the trained program
  8. 8.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) a prediction (c) the model
  9. 9.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a password (c) a label error (d) a prediction
  10. 10.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
  11. 11.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  12. 12.⏩ 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
  13. 13.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) training data (c) a prediction
  14. 14.Which of these is a prediction? (a) recorded spoken words (b) naming a new leaf (c) labelled fruit photos (d) what training builds
  15. 15.⏩ In machine learning, which comes first: 500 labelled leaf photos or naming a new fruit photo? (a) 500 labelled leaf photos (b) naming a new fruit photo
  16. 16.Which of these is training data? (a) naming a new fruit photo (b) tomorrow’s rain guess (c) flagging a new email (d) past weather records
  17. 17.⏩ In machine learning, which comes first: tomorrow’s rain guess or recorded spoken words? (a) tomorrow’s rain guess (b) recorded spoken words
  18. 18.True or false: “past weather records” is training data. (a) False (b) True
  19. 19.⏩ In machine learning, which comes first: 500 labelled leaf photos or tomorrow’s rain guess? (a) 500 labelled leaf photos (b) tomorrow’s rain guess
  20. 20.True or false: “labelled fruit photos” is training data. (a) False (b) True
  21. 21.📦 What happens during training? (a) it takes photos (b) it learns patterns (c) it prints labels (d) it charges up
  22. 22.True or false: “what training builds” is training data. (a) True (b) False
  23. 23.True or false: “typing a new spoken word” is the model. (a) False (b) True
  24. 24.⏩ In machine learning, which comes first: naming a new fruit photo or recorded spoken words? (a) naming a new fruit photo (b) recorded spoken words
  25. 25.True or false: “flagging a new email” is a prediction. (a) False (b) True
  26. 26.⏩ In machine learning, which comes first: the learned patterns or labelled fruit photos? (a) the learned patterns (b) labelled fruit photos
  27. 27.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) prediction, data, model (d) data, model, prediction
  28. 28.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) a prediction (c) the model
  29. 29.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  30. 30.True or false: “flagging a new email” is training data. (a) True (b) False
  31. 31.Which of these is a prediction? (a) tomorrow’s rain guess (b) what training builds (c) past weather records (d) the trained program
  32. 32.True or false: “the learned patterns” is the model. (a) True (b) False
  33. 33.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
  34. 34.True or false: “recorded spoken words” is the model. (a) True (b) False
  35. 35.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  36. 36.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  37. 37.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program
  38. 38.⏩ In machine learning, which comes first: labelled fruit photos or the learned patterns? (a) labelled fruit photos (b) the learned patterns
  39. 39.Which of these is a prediction? (a) past weather records (b) labelled fruit photos (c) naming a new fruit photo (d) old emails marked spam
  40. 40.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) a prediction (c) the model

Answer key

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

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