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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 954 · 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: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
  2. 2.True or false: “tomorrow’s rain guess” is the model. (a) False (b) True
  3. 3.True or false: “recorded spoken words” is a prediction. (a) True (b) False
  4. 4.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
  5. 5.📦 What happens during training? (a) it prints labels (b) it charges up (c) it learns patterns (d) it takes photos
  6. 6.🔁 What is the right order? (a) data, model, prediction (b) model, prediction, data (c) data, prediction, model (d) prediction, data, model
  7. 7.🧪 Why test a model on NEW examples? (a) to change its name (b) to see if it works (c) to make it slower (d) to delete its data
  8. 8.⏩ 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
  9. 9.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  10. 10.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a prediction (c) a password (d) a label error
  11. 11.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  12. 12.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  13. 13.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction
  14. 14.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
  15. 15.⏩ In machine learning, which comes first: old emails marked spam or naming a new leaf? (a) old emails marked spam (b) naming a new leaf
  16. 16.⏩ 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
  17. 17.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  18. 18.True or false: “the learned patterns” is training data. (a) True (b) False
  19. 19.Which of these is a prediction? (a) labelled fruit photos (b) the trained program (c) naming a new fruit photo (d) recorded spoken words
  20. 20.True or false: “recorded spoken words” is training data. (a) True (b) False
  21. 21.Which of these is a prediction? (a) the learned patterns (b) typing a new spoken word (c) labelled fruit photos (d) 500 labelled leaf photos
  22. 22.True or false: “past weather records” is the model. (a) True (b) False
  23. 23.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  24. 24.True or false: “recorded spoken words” is the model. (a) False (b) True
  25. 25.Which of these is a prediction? (a) 500 labelled leaf photos (b) naming a new leaf (c) old emails marked spam (d) what training builds
  26. 26.⏩ In machine learning, which comes first: what training builds or old emails marked spam? (a) what training builds (b) old emails marked spam
  27. 27.Which of these is training data? (a) naming a new fruit photo (b) the trained program (c) old emails marked spam (d) flagging a new email
  28. 28.Which of these is a prediction? (a) 500 labelled leaf photos (b) tomorrow’s rain guess (c) old emails marked spam (d) the learned patterns
  29. 29.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  30. 30.True or false: “the learned patterns” is a prediction. (a) True (b) False
  31. 31.True or false: “the trained program” is the model. (a) False (b) True
  32. 32.Which of these is training data? (a) what training builds (b) naming a new leaf (c) typing a new spoken word (d) recorded spoken words
  33. 33.Which of these is a prediction? (a) labelled fruit photos (b) flagging a new email (c) what training builds (d) 500 labelled leaf photos
  34. 34.⏩ 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
  35. 35.True or false: “what training builds” is training data. (a) True (b) False
  36. 36.True or false: “labelled fruit photos” is training data. (a) True (b) False
  37. 37.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  38. 38.True or false: “500 labelled leaf photos” is the model. (a) True (b) False
  39. 39.True or false: “what training builds” is the model. (a) True (b) False
  40. 40.Which of these is the model? (a) labelled fruit photos (b) what training builds (c) old emails marked spam (d) typing a new spoken word

Answer key

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

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