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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 323 · 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: “what training builds”? (a) the model (b) training data (c) a prediction
  2. 2.Which of these is a prediction? (a) recorded spoken words (b) 500 labelled leaf photos (c) past weather records (d) naming a new leaf
  3. 3.True or false: “the learned patterns” is the model. (a) False (b) True
  4. 4.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  5. 5.True or false: “typing a new spoken word” is training data. (a) False (b) True
  6. 6.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program
  7. 7.Which of these is the model? (a) typing a new spoken word (b) the learned patterns (c) tomorrow’s rain guess (d) naming a new fruit photo
  8. 8.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  9. 9.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to see if it works (d) to change its name
  10. 10.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  11. 11.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) the model (c) training data
  12. 12.True or false: “500 labelled leaf photos” is the model. (a) True (b) False
  13. 13.True or false: “past weather records” is training data. (a) False (b) True
  14. 14.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) training data (c) a password (d) a prediction
  15. 15.Which of these is training data? (a) tomorrow’s rain guess (b) naming a new fruit photo (c) typing a new spoken word (d) old emails marked spam
  16. 16.⏩ In machine learning, which comes first: the learned patterns or naming a new fruit photo? (a) the learned patterns (b) naming a new fruit photo
  17. 17.🔁 What is the right order? (a) data, model, prediction (b) data, prediction, model (c) prediction, data, model (d) model, prediction, data
  18. 18.Which of these is the model? (a) recorded spoken words (b) typing a new spoken word (c) the trained program (d) naming a new leaf
  19. 19.⏩ In machine learning, which comes first: past weather records or naming a new leaf? (a) past weather records (b) naming a new leaf
  20. 20.True or false: “labelled fruit photos” is the model. (a) True (b) False
  21. 21.📦 What happens during training? (a) it learns patterns (b) it charges up (c) it takes photos (d) it prints labels
  22. 22.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  23. 23.⏩ In machine learning, which comes first: recorded spoken words or the trained program? (a) recorded spoken words (b) the trained program
  24. 24.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  25. 25.⏩ In machine learning, which comes first: 500 labelled leaf photos or the trained program? (a) 500 labelled leaf photos (b) the trained program
  26. 26.⏩ In machine learning, which comes first: what training builds or tomorrow’s rain guess? (a) what training builds (b) tomorrow’s rain guess
  27. 27.Which of these is training data? (a) the learned patterns (b) what training builds (c) the trained program (d) recorded spoken words
  28. 28.Which of these is the model? (a) what training builds (b) labelled fruit photos (c) past weather records (d) naming a new leaf
  29. 29.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  30. 30.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  31. 31.Which of these is training data? (a) naming a new leaf (b) the trained program (c) the learned patterns (d) labelled fruit photos
  32. 32.Which of these is training data? (a) tomorrow’s rain guess (b) flagging a new email (c) 500 labelled leaf photos (d) naming a new fruit photo
  33. 33.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) the model (c) a prediction
  34. 34.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) the model (c) training data
  35. 35.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) training data (c) a prediction
  36. 36.True or false: “old emails marked spam” is a prediction. (a) False (b) True
  37. 37.⏩ In machine learning, which comes first: past weather records or what training builds? (a) past weather records (b) what training builds
  38. 38.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
  39. 39.⏩ In machine learning, which comes first: the trained program or 500 labelled leaf photos? (a) the trained program (b) 500 labelled leaf photos
  40. 40.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) the model (c) a prediction

Answer key

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

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