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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 198 · 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: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  2. 2.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  3. 3.Which of these is the model? (a) past weather records (b) recorded spoken words (c) the trained program (d) flagging a new email
  4. 4.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
  5. 5.True or false: “what training builds” is the model. (a) True (b) False
  6. 6.True or false: “the trained program” is training data. (a) False (b) True
  7. 7.⏩ In machine learning, which comes first: what training builds or recorded spoken words? (a) what training builds (b) recorded spoken words
  8. 8.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
  9. 9.Which of these is training data? (a) old emails marked spam (b) what training builds (c) typing a new spoken word (d) naming a new leaf
  10. 10.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
  11. 11.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  12. 12.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  13. 13.Which of these is training data? (a) past weather records (b) naming a new fruit photo (c) the learned patterns (d) the trained program
  14. 14.Which of these is training data? (a) naming a new leaf (b) tomorrow’s rain guess (c) labelled fruit photos (d) typing a new spoken word
  15. 15.⏩ In machine learning, which comes first: labelled fruit photos or naming a new fruit photo? (a) labelled fruit photos (b) naming a new fruit photo
  16. 16.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  17. 17.Which of these is the model? (a) the learned patterns (b) naming a new fruit photo (c) recorded spoken words (d) old emails marked spam
  18. 18.True or false: “labelled fruit photos” is the model. (a) True (b) False
  19. 19.⏩ In machine learning, which comes first: naming a new fruit photo or the learned patterns? (a) naming a new fruit photo (b) the learned patterns
  20. 20.Which of these is training data? (a) flagging a new email (b) the trained program (c) naming a new leaf (d) 500 labelled leaf photos
  21. 21.True or false: “what training builds” is training data. (a) True (b) False
  22. 22.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) training data (c) a prediction
  23. 23.Which of these is training data? (a) typing a new spoken word (b) what training builds (c) the learned patterns (d) recorded spoken words
  24. 24.🧪 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
  25. 25.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a prediction (c) a label error (d) training data
  26. 26.True or false: “labelled fruit photos” is a prediction. (a) False (b) True
  27. 27.True or false: “labelled fruit photos” is training data. (a) True (b) False
  28. 28.⏩ In machine learning, which comes first: past weather records or flagging a new email? (a) past weather records (b) flagging a new email
  29. 29.⏩ In machine learning, which comes first: tomorrow’s rain guess or 500 labelled leaf photos? (a) tomorrow’s rain guess (b) 500 labelled leaf photos
  30. 30.True or false: “the learned patterns” is a prediction. (a) False (b) True
  31. 31.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) a prediction (c) the model
  32. 32.⏩ In machine learning, which comes first: typing a new spoken word or 500 labelled leaf photos? (a) typing a new spoken word (b) 500 labelled leaf photos
  33. 33.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) training data (c) a prediction
  34. 34.True or false: “past weather records” is training data. (a) True (b) False
  35. 35.True or false: “recorded spoken words” is the model. (a) True (b) False
  36. 36.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it takes photos (d) it prints labels
  37. 37.True or false: “flagging a new email” is training data. (a) True (b) False
  38. 38.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  39. 39.⏩ In machine learning, which comes first: labelled fruit photos or typing a new spoken word? (a) labelled fruit photos (b) typing a new spoken word
  40. 40.⏩ In machine learning, which comes first: the trained program or recorded spoken words? (a) the trained program (b) recorded spoken words

Answer key

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

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