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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 614 · 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.True or false: “the learned patterns” is training data. (a) True (b) False
  2. 2.Which of these is the model? (a) tomorrow’s rain guess (b) recorded spoken words (c) what training builds (d) flagging a new email
  3. 3.🧪 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
  4. 4.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
  5. 5.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
  6. 6.Which of these is training data? (a) the trained program (b) naming a new fruit photo (c) old emails marked spam (d) typing a new spoken word
  7. 7.True or false: “naming a new leaf” is the model. (a) True (b) False
  8. 8.True or false: “old emails marked spam” is training data. (a) True (b) False
  9. 9.⏩ In machine learning, which comes first: naming a new leaf or recorded spoken words? (a) naming a new leaf (b) recorded spoken words
  10. 10.True or false: “the learned patterns” is the model. (a) False (b) True
  11. 11.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
  12. 12.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
  13. 13.True or false: “past weather records” is a prediction. (a) False (b) True
  14. 14.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  15. 15.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
  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.🔁 What is the right order? (a) model, prediction, data (b) data, prediction, model (c) prediction, data, model (d) data, model, prediction
  18. 18.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model
  19. 19.Which of these is a prediction? (a) the trained program (b) recorded spoken words (c) flagging a new email (d) old emails marked spam
  20. 20.🔮 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
  21. 21.Which of these is training data? (a) flagging a new email (b) 500 labelled leaf photos (c) the learned patterns (d) naming a new leaf
  22. 22.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) the model (c) a prediction
  23. 23.Which of these is training data? (a) the trained program (b) typing a new spoken word (c) recorded spoken words (d) tomorrow’s rain guess
  24. 24.Which of these is the model? (a) recorded spoken words (b) typing a new spoken word (c) flagging a new email (d) the learned patterns
  25. 25.⏩ In machine learning, which comes first: the trained program or flagging a new email? (a) the trained program (b) flagging a new email
  26. 26.Which of these is training data? (a) the trained program (b) tomorrow’s rain guess (c) the learned patterns (d) past weather records
  27. 27.Which of these is a prediction? (a) the learned patterns (b) naming a new leaf (c) old emails marked spam (d) recorded spoken words
  28. 28.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  29. 29.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  30. 30.Which of these is the model? (a) naming a new fruit photo (b) the trained program (c) flagging a new email (d) old emails marked spam
  31. 31.True or false: “past weather records” is the model. (a) False (b) True
  32. 32.True or false: “recorded spoken words” is a prediction. (a) True (b) False
  33. 33.Which of these is a prediction? (a) the trained program (b) what training builds (c) past weather records (d) tomorrow’s rain guess
  34. 34.True or false: “the trained program” is training data. (a) False (b) True
  35. 35.⏩ In machine learning, which comes first: past weather records or the learned patterns? (a) past weather records (b) the learned patterns
  36. 36.⏩ In machine learning, which comes first: the trained program or past weather records? (a) the trained program (b) past weather records
  37. 37.⏩ In machine learning, which comes first: flagging a new email or 500 labelled leaf photos? (a) flagging a new email (b) 500 labelled leaf photos
  38. 38.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  39. 39.True or false: “labelled fruit photos” is the model. (a) True (b) False
  40. 40.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns

Answer key

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

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