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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 541 · 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) a prediction (b) the model (c) training data
  2. 2.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  3. 3.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to change its name (d) to delete its data
  4. 4.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) training data (c) a prediction
  5. 5.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
  6. 6.⏩ In machine learning, which comes first: past weather records or naming a new fruit photo? (a) past weather records (b) naming a new fruit photo
  7. 7.Which of these is a prediction? (a) 500 labelled leaf photos (b) recorded spoken words (c) past weather records (d) typing a new spoken word
  8. 8.Which of these is training data? (a) typing a new spoken word (b) what training builds (c) tomorrow’s rain guess (d) labelled fruit photos
  9. 9.True or false: “the learned patterns” is training data. (a) True (b) False
  10. 10.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  11. 11.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, prediction, model (d) data, model, prediction
  12. 12.Which of these is training data? (a) the learned patterns (b) flagging a new email (c) naming a new fruit photo (d) recorded spoken words
  13. 13.Which of these is the model? (a) labelled fruit photos (b) old emails marked spam (c) past weather records (d) the trained program
  14. 14.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
  15. 15.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) training data (c) a prediction
  16. 16.⏩ In machine learning, which comes first: the learned patterns or old emails marked spam? (a) the learned patterns (b) old emails marked spam
  17. 17.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  18. 18.🔮 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
  19. 19.Which of these is training data? (a) the trained program (b) 500 labelled leaf photos (c) what training builds (d) naming a new fruit photo
  20. 20.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False
  21. 21.True or false: “500 labelled leaf photos” is a prediction. (a) True (b) False
  22. 22.📦 What happens during training? (a) it charges up (b) it takes photos (c) it learns patterns (d) it prints labels
  23. 23.⏩ 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
  24. 24.Which of these is a prediction? (a) naming a new fruit photo (b) past weather records (c) the trained program (d) 500 labelled leaf photos
  25. 25.⏩ In machine learning, which comes first: the trained program or recorded spoken words? (a) the trained program (b) recorded spoken words
  26. 26.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  27. 27.Which of these is the model? (a) the learned patterns (b) tomorrow’s rain guess (c) recorded spoken words (d) typing a new spoken word
  28. 28.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
  29. 29.True or false: “the trained program” is the model. (a) True (b) False
  30. 30.True or false: “flagging a new email” is a prediction. (a) False (b) True
  31. 31.True or false: “past weather records” is training data. (a) True (b) False
  32. 32.⏩ In machine learning, which comes first: recorded spoken words or the trained program? (a) recorded spoken words (b) the trained program
  33. 33.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  34. 34.True or false: “the learned patterns” is the model. (a) False (b) True
  35. 35.Which of these is a prediction? (a) naming a new leaf (b) what training builds (c) 500 labelled leaf photos (d) the learned patterns
  36. 36.⏩ In machine learning, which comes first: old emails marked spam or the learned patterns? (a) old emails marked spam (b) the learned patterns
  37. 37.True or false: “naming a new leaf” is a prediction. (a) True (b) False
  38. 38.True or false: “typing a new spoken word” is the model. (a) False (b) True
  39. 39.⏩ In machine learning, which comes first: past weather records or flagging a new email? (a) past weather records (b) flagging a new email
  40. 40.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True

Answer key

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

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