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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 575 · 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.Which of these is training data? (a) flagging a new email (b) past weather records (c) the learned patterns (d) naming a new fruit photo
  2. 2.⏩ In machine learning, which comes first: naming a new fruit photo or past weather records? (a) naming a new fruit photo (b) past weather records
  3. 3.⏩ In machine learning, which comes first: old emails marked spam or naming a new leaf? (a) old emails marked spam (b) naming a new leaf
  4. 4.Which of these is a prediction? (a) the learned patterns (b) tomorrow’s rain guess (c) recorded spoken words (d) old emails marked spam
  5. 5.🧪 Why test a model on NEW examples? (a) to make it slower (b) to delete its data (c) to change its name (d) to see if it works
  6. 6.Which of these is a prediction? (a) past weather records (b) recorded spoken words (c) typing a new spoken word (d) the trained program
  7. 7.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
  8. 8.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False
  9. 9.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) the model (c) a prediction
  10. 10.Which of these is training data? (a) the learned patterns (b) old emails marked spam (c) naming a new fruit photo (d) what training builds
  11. 11.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  12. 12.Which of these is the model? (a) the trained program (b) recorded spoken words (c) tomorrow’s rain guess (d) old emails marked spam
  13. 13.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  14. 14.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  15. 15.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  16. 16.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  17. 17.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  18. 18.True or false: “what training builds” is training data. (a) False (b) True
  19. 19.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
  20. 20.True or false: “labelled fruit photos” is training data. (a) True (b) False
  21. 21.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
  22. 22.True or false: “naming a new leaf” is a prediction. (a) False (b) True
  23. 23.Which of these is the model? (a) old emails marked spam (b) naming a new fruit photo (c) the learned patterns (d) recorded spoken words
  24. 24.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
  25. 25.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) training data (c) a prediction (d) a password
  26. 26.Which of these is a prediction? (a) old emails marked spam (b) what training builds (c) naming a new fruit photo (d) 500 labelled leaf photos
  27. 27.📦 What happens during training? (a) it prints labels (b) it learns patterns (c) it takes photos (d) it charges up
  28. 28.⏩ In machine learning, which comes first: labelled fruit photos or what training builds? (a) labelled fruit photos (b) what training builds
  29. 29.True or false: “naming a new leaf” is training data. (a) True (b) False
  30. 30.True or false: “recorded spoken words” is training data. (a) False (b) True
  31. 31.🔁 What is the right order? (a) data, model, prediction (b) prediction, data, model (c) model, prediction, data (d) data, prediction, model
  32. 32.True or false: “the learned patterns” is the model. (a) False (b) True
  33. 33.True or false: “old emails marked spam” is training data. (a) True (b) False
  34. 34.Which of these is the model? (a) typing a new spoken word (b) old emails marked spam (c) 500 labelled leaf photos (d) what training builds
  35. 35.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) the model (c) training data
  36. 36.⏩ In machine learning, which comes first: old emails marked spam or typing a new spoken word? (a) old emails marked spam (b) typing a new spoken word
  37. 37.⏩ In machine learning, which comes first: 500 labelled leaf photos or the learned patterns? (a) 500 labelled leaf photos (b) the learned patterns
  38. 38.⏩ In machine learning, which comes first: past weather records or flagging a new email? (a) past weather records (b) flagging a new email
  39. 39.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  40. 40.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) training data (c) a prediction

Answer key

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

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