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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 806 · 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: labelled fruit photos or typing a new spoken word? (a) labelled fruit photos (b) typing a new spoken word
  2. 2.🧪 Why test a model on NEW examples? (a) to make it slower (b) to delete its data (c) to change its name (d) to see if it works
  3. 3.⏩ In machine learning, which comes first: flagging a new email or labelled fruit photos? (a) flagging a new email (b) labelled fruit photos
  4. 4.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  5. 5.Which of these is a prediction? (a) 500 labelled leaf photos (b) labelled fruit photos (c) the trained program (d) naming a new fruit photo
  6. 6.True or false: “old emails marked spam” is training data. (a) False (b) True
  7. 7.Which of these is training data? (a) the learned patterns (b) the trained program (c) past weather records (d) what training builds
  8. 8.True or false: “past weather records” is training data. (a) False (b) True
  9. 9.Which of these is the model? (a) old emails marked spam (b) naming a new fruit photo (c) the learned patterns (d) tomorrow’s rain guess
  10. 10.⏩ In machine learning, which comes first: the trained program or past weather records? (a) the trained program (b) past weather records
  11. 11.⏩ 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
  12. 12.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  13. 13.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a password (c) a prediction (d) training data
  14. 14.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  15. 15.Which of these is training data? (a) tomorrow’s rain guess (b) naming a new fruit photo (c) old emails marked spam (d) typing a new spoken word
  16. 16.True or false: “typing a new spoken word” is training data. (a) True (b) False
  17. 17.Which of these is a prediction? (a) past weather records (b) the trained program (c) recorded spoken words (d) naming a new leaf
  18. 18.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  19. 19.Which of these is a prediction? (a) past weather records (b) labelled fruit photos (c) recorded spoken words (d) flagging a new email
  20. 20.True or false: “recorded spoken words” is the model. (a) True (b) False
  21. 21.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) data, prediction, model (d) prediction, data, model
  22. 22.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) training data (c) a prediction
  23. 23.True or false: “the trained program” is the model. (a) False (b) True
  24. 24.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
  25. 25.Which of these is a prediction? (a) typing a new spoken word (b) the trained program (c) recorded spoken words (d) labelled fruit photos
  26. 26.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  27. 27.True or false: “what training builds” is training data. (a) False (b) True
  28. 28.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) training data (c) a prediction
  29. 29.⏩ In machine learning, which comes first: 500 labelled leaf photos or flagging a new email? (a) 500 labelled leaf photos (b) flagging a new email
  30. 30.⏩ 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
  31. 31.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  32. 32.⏩ In machine learning, which comes first: what training builds or labelled fruit photos? (a) what training builds (b) labelled fruit photos
  33. 33.⏩ In machine learning, which comes first: the learned patterns or old emails marked spam? (a) the learned patterns (b) old emails marked spam
  34. 34.Which of these is training data? (a) flagging a new email (b) what training builds (c) the learned patterns (d) 500 labelled leaf photos
  35. 35.📦 What happens during training? (a) it prints labels (b) it takes photos (c) it learns patterns (d) it charges up
  36. 36.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
  37. 37.True or false: “the learned patterns” is the model. (a) False (b) True
  38. 38.True or false: “past weather records” is the model. (a) True (b) False
  39. 39.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  40. 40.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns

Answer key

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

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