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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 54 · 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 learns patterns (b) it takes photos (c) it charges up (d) it prints labels
  2. 2.🧪 Why test a model on NEW examples? (a) to change its name (b) to delete its data (c) to make it slower (d) to see if it works
  3. 3.Which of these is the model? (a) 500 labelled leaf photos (b) recorded spoken words (c) the learned patterns (d) labelled fruit photos
  4. 4.⏩ 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
  5. 5.True or false: “recorded spoken words” is a prediction. (a) True (b) False
  6. 6.Which of these is training data? (a) what training builds (b) naming a new leaf (c) 500 labelled leaf photos (d) flagging a new email
  7. 7.⏩ In machine learning, which comes first: labelled fruit photos or the trained program? (a) labelled fruit photos (b) the trained program
  8. 8.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
  9. 9.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  10. 10.Which of these is training data? (a) the learned patterns (b) typing a new spoken word (c) tomorrow’s rain guess (d) past weather records
  11. 11.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  12. 12.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
  13. 13.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  14. 14.⏩ In machine learning, which comes first: 500 labelled leaf photos or the learned patterns? (a) 500 labelled leaf photos (b) the learned patterns
  15. 15.True or false: “recorded spoken words” is the model. (a) True (b) False
  16. 16.🔁 Training data, the model or a prediction: “labelled fruit 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.Which of these is a prediction? (a) the trained program (b) flagging a new email (c) 500 labelled leaf photos (d) what training builds
  19. 19.True or false: “500 labelled leaf photos” is the model. (a) True (b) False
  20. 20.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  21. 21.True or false: “past weather records” is the model. (a) False (b) True
  22. 22.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
  23. 23.True or false: “old emails marked spam” is a prediction. (a) False (b) True
  24. 24.Which of these is a prediction? (a) labelled fruit photos (b) old emails marked spam (c) typing a new spoken word (d) the learned patterns
  25. 25.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) a prediction (c) the model
  26. 26.⏩ In machine learning, which comes first: typing a new spoken word or what training builds? (a) typing a new spoken word (b) what training builds
  27. 27.True or false: “naming a new fruit photo” is the model. (a) False (b) True
  28. 28.⏩ In machine learning, which comes first: the trained program or recorded spoken words? (a) the trained program (b) recorded spoken words
  29. 29.⏩ 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
  30. 30.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  31. 31.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
  32. 32.🔁 What is the right order? (a) model, prediction, data (b) data, prediction, model (c) data, model, prediction (d) prediction, data, model
  33. 33.Which of these is the model? (a) labelled fruit photos (b) the trained program (c) naming a new leaf (d) 500 labelled leaf photos
  34. 34.True or false: “labelled fruit photos” is training data. (a) True (b) False
  35. 35.True or false: “the trained program” is the model. (a) False (b) True
  36. 36.True or false: “what training builds” is the model. (a) True (b) False
  37. 37.Which of these is a prediction? (a) naming a new leaf (b) 500 labelled leaf photos (c) what training builds (d) labelled fruit photos
  38. 38.⏩ In machine learning, which comes first: tomorrow’s rain guess or past weather records? (a) tomorrow’s rain guess (b) past weather records
  39. 39.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  40. 40.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data

Answer key

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

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