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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 171 · 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.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  2. 2.🔮 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
  3. 3.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to see if it works (d) to change its name
  4. 4.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  5. 5.True or false: “labelled fruit photos” is the model. (a) True (b) False
  6. 6.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  7. 7.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  8. 8.⏩ In machine learning, which comes first: what training builds or typing a new spoken word? (a) what training builds (b) typing a new spoken word
  9. 9.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  10. 10.Which of these is training data? (a) recorded spoken words (b) what training builds (c) the trained program (d) typing a new spoken word
  11. 11.Which of these is training data? (a) flagging a new email (b) tomorrow’s rain guess (c) 500 labelled leaf photos (d) what training builds
  12. 12.⏩ In machine learning, which comes first: what training builds or past weather records? (a) what training builds (b) past weather records
  13. 13.⏩ In machine learning, which comes first: the learned patterns or labelled fruit photos? (a) the learned patterns (b) labelled fruit photos
  14. 14.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  15. 15.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) training data (c) the model
  16. 16.Which of these is a prediction? (a) tomorrow’s rain guess (b) past weather records (c) recorded spoken words (d) old emails marked spam
  17. 17.🔁 What is the right order? (a) data, prediction, model (b) model, prediction, data (c) prediction, data, model (d) data, model, prediction
  18. 18.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) a prediction (c) the model
  19. 19.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  20. 20.Which of these is the model? (a) tomorrow’s rain guess (b) typing a new spoken word (c) flagging a new email (d) the trained program
  21. 21.True or false: “naming a new fruit photo” is a prediction. (a) False (b) True
  22. 22.Which of these is a prediction? (a) old emails marked spam (b) the trained program (c) past weather records (d) naming a new fruit photo
  23. 23.True or false: “the learned patterns” is the model. (a) True (b) False
  24. 24.True or false: “old emails marked spam” is training data. (a) False (b) True
  25. 25.Which of these is a prediction? (a) typing a new spoken word (b) the trained program (c) what training builds (d) old emails marked spam
  26. 26.True or false: “flagging a new email” is a prediction. (a) True (b) False
  27. 27.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  28. 28.True or false: “past weather records” is a prediction. (a) False (b) True
  29. 29.True or false: “recorded spoken words” is training data. (a) False (b) True
  30. 30.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  31. 31.True or false: “typing a new spoken word” is training data. (a) True (b) False
  32. 32.📦 What happens during training? (a) it prints labels (b) it learns patterns (c) it charges up (d) it takes photos
  33. 33.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  34. 34.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  35. 35.Which of these is the model? (a) old emails marked spam (b) naming a new leaf (c) what training builds (d) naming a new fruit photo
  36. 36.⏩ In machine learning, which comes first: labelled fruit photos or flagging a new email? (a) labelled fruit photos (b) flagging a new email
  37. 37.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  38. 38.True or false: “old emails marked spam” is the model. (a) False (b) True
  39. 39.⏩ In machine learning, which comes first: naming a new fruit photo or what training builds? (a) naming a new fruit photo (b) what training builds
  40. 40.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) training data (c) a prediction

Answer key

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

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