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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 927 · 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: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
  2. 2.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
  3. 3.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
  4. 4.⏩ 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
  5. 5.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  6. 6.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) training data (c) the model
  7. 7.Which of these is training data? (a) past weather records (b) flagging a new email (c) tomorrow’s rain guess (d) the learned patterns
  8. 8.⏩ In machine learning, which comes first: labelled fruit photos or the trained program? (a) labelled fruit photos (b) the trained program
  9. 9.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to see if it works (d) to make it slower
  10. 10.Which of these is a prediction? (a) the trained program (b) the learned patterns (c) what training builds (d) tomorrow’s rain guess
  11. 11.⏩ In machine learning, which comes first: past weather records or naming a new leaf? (a) past weather records (b) naming a new leaf
  12. 12.Which of these is a prediction? (a) naming a new leaf (b) recorded spoken words (c) labelled fruit photos (d) 500 labelled leaf photos
  13. 13.True or false: “flagging a new email” is a prediction. (a) True (b) False
  14. 14.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
  15. 15.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  16. 16.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) training data (c) the model
  17. 17.🔮 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
  18. 18.True or false: “the trained program” is a prediction. (a) True (b) False
  19. 19.📦 What happens during training? (a) it takes photos (b) it prints labels (c) it charges up (d) it learns patterns
  20. 20.Which of these is the model? (a) the trained program (b) typing a new spoken word (c) old emails marked spam (d) recorded spoken words
  21. 21.Which of these is the model? (a) what training builds (b) recorded spoken words (c) naming a new leaf (d) labelled fruit photos
  22. 22.True or false: “the trained program” is training data. (a) False (b) True
  23. 23.⏩ 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
  24. 24.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) training data (c) a prediction
  25. 25.Which of these is training data? (a) what training builds (b) the trained program (c) recorded spoken words (d) tomorrow’s rain guess
  26. 26.⏩ In machine learning, which comes first: naming a new fruit photo or the trained program? (a) naming a new fruit photo (b) the trained program
  27. 27.True or false: “typing a new spoken word” is the model. (a) False (b) True
  28. 28.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, model, prediction (d) data, prediction, model
  29. 29.True or false: “naming a new leaf” is the model. (a) False (b) True
  30. 30.Which of these is training data? (a) typing a new spoken word (b) labelled fruit photos (c) naming a new leaf (d) naming a new fruit photo
  31. 31.True or false: “the learned patterns” is training data. (a) True (b) False
  32. 32.True or false: “past weather records” is the model. (a) False (b) True
  33. 33.⏩ 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
  34. 34.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
  35. 35.Which of these is the model? (a) naming a new leaf (b) the learned patterns (c) recorded spoken words (d) old emails marked spam
  36. 36.True or false: “what training builds” is a prediction. (a) False (b) True
  37. 37.Which of these is training data? (a) naming a new fruit photo (b) 500 labelled leaf photos (c) the learned patterns (d) naming a new leaf
  38. 38.⏩ In machine learning, which comes first: labelled fruit photos or naming a new leaf? (a) labelled fruit photos (b) naming a new leaf
  39. 39.True or false: “what training builds” is training data. (a) True (b) False
  40. 40.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction

Answer key

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

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