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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 579 · 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.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to delete its data (d) to change its name
  2. 2.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) training data (c) the model
  3. 3.📦 What happens during training? (a) it prints labels (b) it learns patterns (c) it takes photos (d) it charges up
  4. 4.True or false: “tomorrow’s rain guess” is training data. (a) False (b) True
  5. 5.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) training data (c) the model
  6. 6.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  7. 7.True or false: “naming a new leaf” is the model. (a) False (b) True
  8. 8.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  9. 9.True or false: “recorded spoken words” is a prediction. (a) False (b) True
  10. 10.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  11. 11.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction
  12. 12.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  13. 13.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  14. 14.True or false: “typing a new spoken word” is the model. (a) False (b) True
  15. 15.Which of these is training data? (a) naming a new fruit photo (b) 500 labelled leaf photos (c) naming a new leaf (d) typing a new spoken word
  16. 16.Which of these is training data? (a) tomorrow’s rain guess (b) old emails marked spam (c) typing a new spoken word (d) the learned patterns
  17. 17.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  18. 18.Which of these is training data? (a) naming a new leaf (b) tomorrow’s rain guess (c) flagging a new email (d) recorded spoken words
  19. 19.True or false: “recorded spoken words” is training data. (a) False (b) True
  20. 20.⏩ 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
  21. 21.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) the model (c) training data
  22. 22.🔮 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
  23. 23.Which of these is a prediction? (a) typing a new spoken word (b) the learned patterns (c) the trained program (d) labelled fruit photos
  24. 24.Which of these is a prediction? (a) 500 labelled leaf photos (b) flagging a new email (c) the trained program (d) what training builds
  25. 25.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
  26. 26.⏩ In machine learning, which comes first: the trained program or 500 labelled leaf photos? (a) the trained program (b) 500 labelled leaf photos
  27. 27.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) the model (c) a prediction
  28. 28.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
  29. 29.⏩ In machine learning, which comes first: flagging a new email or old emails marked spam? (a) flagging a new email (b) old emails marked spam
  30. 30.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) training data (c) a prediction
  31. 31.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  32. 32.Which of these is the model? (a) the trained program (b) flagging a new email (c) old emails marked spam (d) past weather records
  33. 33.True or false: “flagging a new email” is a prediction. (a) False (b) True
  34. 34.⏩ 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
  35. 35.True or false: “flagging a new email” is training data. (a) False (b) True
  36. 36.True or false: “the learned patterns” is the model. (a) True (b) False
  37. 37.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
  38. 38.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  39. 39.Which of these is the model? (a) recorded spoken words (b) what training builds (c) naming a new leaf (d) naming a new fruit photo
  40. 40.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) data, prediction, model (d) model, prediction, data

Answer key

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

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