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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 933 · 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.📦 What happens during training? (a) it prints labels (b) it takes photos (c) it charges up (d) it learns patterns
  2. 2.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) data, prediction, model (d) model, prediction, data
  3. 3.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  4. 4.True or false: “recorded spoken words” is a prediction. (a) False (b) True
  5. 5.🧪 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
  6. 6.Which of these is a prediction? (a) naming a new leaf (b) old emails marked spam (c) recorded spoken words (d) 500 labelled leaf photos
  7. 7.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  8. 8.Which of these is the model? (a) naming a new fruit photo (b) what training builds (c) typing a new spoken word (d) naming a new leaf
  9. 9.True or false: “flagging a new email” is the model. (a) False (b) True
  10. 10.⏩ In machine learning, which comes first: recorded spoken words or the learned patterns? (a) recorded spoken words (b) the learned patterns
  11. 11.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model
  12. 12.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  13. 13.⏩ 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
  14. 14.Which of these is the model? (a) naming a new leaf (b) the trained program (c) tomorrow’s rain guess (d) flagging a new email
  15. 15.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a prediction (c) a label error (d) training data
  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.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  18. 18.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program
  19. 19.⏩ In machine learning, which comes first: naming a new leaf or past weather records? (a) naming a new leaf (b) past weather records
  20. 20.⏩ In machine learning, which comes first: tomorrow’s rain guess or past weather records? (a) tomorrow’s rain guess (b) past weather records
  21. 21.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
  22. 22.Which of these is the model? (a) tomorrow’s rain guess (b) the learned patterns (c) naming a new leaf (d) recorded spoken words
  23. 23.True or false: “the learned patterns” is training data. (a) True (b) False
  24. 24.Which of these is a prediction? (a) the learned patterns (b) flagging a new email (c) old emails marked spam (d) the trained program
  25. 25.True or false: “old emails marked spam” is training data. (a) True (b) False
  26. 26.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
  27. 27.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) the model (c) a prediction
  28. 28.⏩ 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
  29. 29.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  30. 30.Which of these is training data? (a) flagging a new email (b) naming a new fruit photo (c) old emails marked spam (d) the learned patterns
  31. 31.Which of these is a prediction? (a) tomorrow’s rain guess (b) old emails marked spam (c) labelled fruit photos (d) recorded spoken words
  32. 32.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) the model (c) a prediction
  33. 33.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  34. 34.⏩ In machine learning, which comes first: labelled fruit photos or naming a new fruit photo? (a) labelled fruit photos (b) naming a new fruit photo
  35. 35.True or false: “naming a new fruit photo” is training data. (a) True (b) False
  36. 36.True or false: “flagging a new email” is a prediction. (a) False (b) True
  37. 37.⏩ In machine learning, which comes first: recorded spoken words or naming a new fruit photo? (a) recorded spoken words (b) naming a new fruit photo
  38. 38.Which of these is training data? (a) naming a new leaf (b) flagging a new email (c) labelled fruit photos (d) naming a new fruit photo
  39. 39.True or false: “past weather records” is the model. (a) False (b) True
  40. 40.⏩ In machine learning, which comes first: 500 labelled leaf photos or typing a new spoken word? (a) 500 labelled leaf photos (b) typing a new spoken word

Answer key

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

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