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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 192 · 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: “tomorrow’s rain guess”? (a) the model (b) a prediction (c) training data
  2. 2.Which of these is training data? (a) the trained program (b) tomorrow’s rain guess (c) 500 labelled leaf photos (d) the learned patterns
  3. 3.Which of these is a prediction? (a) typing a new spoken word (b) the trained program (c) labelled fruit photos (d) recorded spoken words
  4. 4.📦 What happens during training? (a) it takes photos (b) it charges up (c) it learns patterns (d) it prints labels
  5. 5.Which of these is the model? (a) tomorrow’s rain guess (b) the trained program (c) naming a new fruit photo (d) old emails marked spam
  6. 6.⏩ In machine learning, which comes first: the learned patterns or old emails marked spam? (a) the learned patterns (b) old emails marked spam
  7. 7.Which of these is a prediction? (a) the trained program (b) flagging a new email (c) 500 labelled leaf photos (d) old emails marked spam
  8. 8.🧪 Why test a model on NEW examples? (a) to see if it works (b) to make it slower (c) to delete its data (d) to change its name
  9. 9.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) a prediction (c) the model
  10. 10.True or false: “the learned patterns” is training data. (a) False (b) True
  11. 11.⏩ In machine learning, which comes first: naming a new leaf or old emails marked spam? (a) naming a new leaf (b) old emails marked spam
  12. 12.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
  13. 13.True or false: “old emails marked spam” is training data. (a) False (b) True
  14. 14.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
  15. 15.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  16. 16.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) training data (c) the model
  17. 17.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
  18. 18.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False
  19. 19.Which of these is the model? (a) labelled fruit photos (b) recorded spoken words (c) the learned patterns (d) naming a new leaf
  20. 20.Which of these is training data? (a) flagging a new email (b) naming a new leaf (c) the trained program (d) recorded spoken words
  21. 21.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, model, prediction (d) data, prediction, model
  22. 22.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  23. 23.True or false: “the trained program” is the model. (a) False (b) True
  24. 24.⏩ In machine learning, which comes first: flagging a new email or recorded spoken words? (a) flagging a new email (b) recorded spoken words
  25. 25.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
  26. 26.Which of these is training data? (a) what training builds (b) naming a new fruit photo (c) typing a new spoken word (d) old emails marked spam
  27. 27.Which of these is the model? (a) typing a new spoken word (b) what training builds (c) past weather records (d) flagging a new email
  28. 28.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess
  29. 29.True or false: “recorded spoken words” is a prediction. (a) True (b) False
  30. 30.Which of these is training data? (a) what training builds (b) naming a new leaf (c) past weather records (d) the trained program
  31. 31.Which of these is training data? (a) typing a new spoken word (b) naming a new fruit photo (c) the trained program (d) labelled fruit photos
  32. 32.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  33. 33.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
  34. 34.⏩ 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
  35. 35.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) training data (c) a label error (d) a prediction
  36. 36.⏩ In machine learning, which comes first: the trained program or flagging a new email? (a) the trained program (b) flagging a new email
  37. 37.Which of these is a prediction? (a) labelled fruit photos (b) the learned patterns (c) tomorrow’s rain guess (d) recorded spoken words
  38. 38.⏩ In machine learning, which comes first: past weather records or naming a new leaf? (a) past weather records (b) naming a new leaf
  39. 39.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
  40. 40.True or false: “tomorrow’s rain guess” is training data. (a) True (b) False

Answer key

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

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