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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 136 · 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: “typing a new spoken word” is a prediction. (a) False (b) True
  2. 2.Which of these is a prediction? (a) labelled fruit photos (b) the learned patterns (c) flagging a new email (d) recorded spoken words
  3. 3.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
  4. 4.Which of these is training data? (a) the learned patterns (b) past weather records (c) naming a new leaf (d) what training builds
  5. 5.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
  6. 6.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a password (c) a prediction (d) a label error
  7. 7.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to delete its data (d) to see if it works
  8. 8.True or false: “labelled fruit photos” is training data. (a) True (b) False
  9. 9.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) a prediction (c) the model
  10. 10.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
  11. 11.⏩ In machine learning, which comes first: 500 labelled leaf photos or the trained program? (a) 500 labelled leaf photos (b) the trained program
  12. 12.Which of these is a prediction? (a) 500 labelled leaf photos (b) old emails marked spam (c) recorded spoken words (d) naming a new leaf
  13. 13.⏩ In machine learning, which comes first: naming a new fruit photo or the trained program? (a) naming a new fruit photo (b) the trained program
  14. 14.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  15. 15.Which of these is training data? (a) the trained program (b) naming a new leaf (c) what training builds (d) recorded spoken words
  16. 16.📦 What happens during training? (a) it learns patterns (b) it takes photos (c) it charges up (d) it prints labels
  17. 17.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  18. 18.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) training data (c) a prediction
  19. 19.⏩ In machine learning, which comes first: typing a new spoken word or the learned patterns? (a) typing a new spoken word (b) the learned patterns
  20. 20.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  21. 21.Which of these is the model? (a) labelled fruit photos (b) old emails marked spam (c) what training builds (d) recorded spoken words
  22. 22.Which of these is training data? (a) old emails marked spam (b) naming a new leaf (c) what training builds (d) the trained program
  23. 23.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
  24. 24.Which of these is the model? (a) the learned patterns (b) past weather records (c) labelled fruit photos (d) recorded spoken words
  25. 25.True or false: “what training builds” is a prediction. (a) True (b) False
  26. 26.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
  27. 27.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) data, prediction, model (d) model, prediction, data
  28. 28.⏩ In machine learning, which comes first: 500 labelled leaf photos or typing a new spoken word? (a) 500 labelled leaf photos (b) typing a new spoken word
  29. 29.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program
  30. 30.True or false: “flagging a new email” is the model. (a) True (b) False
  31. 31.True or false: “the trained program” is the model. (a) True (b) False
  32. 32.True or false: “the trained program” is training data. (a) True (b) False
  33. 33.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  34. 34.Which of these is training data? (a) the trained program (b) naming a new fruit photo (c) typing a new spoken word (d) 500 labelled leaf photos
  35. 35.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  36. 36.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) a prediction (c) training data
  37. 37.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  38. 38.⏩ In machine learning, which comes first: the learned patterns or recorded spoken words? (a) the learned patterns (b) recorded spoken words
  39. 39.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  40. 40.True or false: “naming a new fruit photo” is training data. (a) True (b) False

Answer key

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

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