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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 625 · 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: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  2. 2.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) model, prediction, data (d) data, model, prediction
  3. 3.True or false: “the trained program” is the model. (a) True (b) False
  4. 4.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to see if it works (d) to delete its data
  5. 5.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) the model (c) training data
  6. 6.Which of these is training data? (a) naming a new fruit photo (b) the learned patterns (c) flagging a new email (d) past weather records
  7. 7.⏩ In machine learning, which comes first: 500 labelled leaf photos or the learned patterns? (a) 500 labelled leaf photos (b) the learned patterns
  8. 8.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  9. 9.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) training data (c) a prediction (d) a label error
  10. 10.True or false: “recorded spoken words” is the model. (a) False (b) True
  11. 11.True or false: “recorded spoken words” is training data. (a) True (b) False
  12. 12.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  13. 13.Which of these is training data? (a) 500 labelled leaf photos (b) the learned patterns (c) tomorrow’s rain guess (d) the trained program
  14. 14.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) training data (c) a prediction
  15. 15.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
  16. 16.True or false: “flagging a new email” is the model. (a) True (b) False
  17. 17.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  18. 18.⏩ In machine learning, which comes first: flagging a new email or past weather records? (a) flagging a new email (b) past weather records
  19. 19.⏩ In machine learning, which comes first: the trained program or typing a new spoken word? (a) the trained program (b) typing a new spoken word
  20. 20.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) training data (c) a prediction
  21. 21.Which of these is training data? (a) what training builds (b) naming a new leaf (c) the learned patterns (d) old emails marked spam
  22. 22.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
  23. 23.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
  24. 24.Which of these is a prediction? (a) typing a new spoken word (b) labelled fruit photos (c) what training builds (d) recorded spoken words
  25. 25.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  26. 26.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  27. 27.True or false: “past weather records” is training data. (a) True (b) False
  28. 28.📦 What happens during training? (a) it charges up (b) it takes photos (c) it prints labels (d) it learns patterns
  29. 29.Which of these is training data? (a) the trained program (b) recorded spoken words (c) the learned patterns (d) naming a new fruit photo
  30. 30.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  31. 31.⏩ In machine learning, which comes first: what training builds or recorded spoken words? (a) what training builds (b) recorded spoken words
  32. 32.True or false: “the learned patterns” is the model. (a) False (b) True
  33. 33.Which of these is training data? (a) typing a new spoken word (b) naming a new fruit photo (c) labelled fruit photos (d) naming a new leaf
  34. 34.True or false: “what training builds” is the model. (a) False (b) True
  35. 35.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  36. 36.Which of these is a prediction? (a) what training builds (b) the learned patterns (c) naming a new leaf (d) old emails marked spam
  37. 37.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  38. 38.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  39. 39.True or false: “old emails marked spam” is a prediction. (a) True (b) False
  40. 40.True or false: “500 labelled leaf photos” is the model. (a) False (b) True

Answer key

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

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