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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 432 · 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: “naming a new leaf” is training data. (a) False (b) True
  2. 2.📦 What happens during training? (a) it prints labels (b) it takes photos (c) it charges up (d) it learns patterns
  3. 3.Which of these is a prediction? (a) the learned patterns (b) past weather records (c) recorded spoken words (d) tomorrow’s rain guess
  4. 4.🧪 Why test a model on NEW examples? (a) to see if it works (b) to change its name (c) to make it slower (d) to delete its data
  5. 5.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  6. 6.True or false: “recorded spoken words” is the model. (a) True (b) False
  7. 7.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  8. 8.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  9. 9.Which of these is training data? (a) typing a new spoken word (b) tomorrow’s rain guess (c) the trained program (d) recorded spoken words
  10. 10.Which of these is a prediction? (a) what training builds (b) typing a new spoken word (c) 500 labelled leaf photos (d) past weather records
  11. 11.Which of these is the model? (a) tomorrow’s rain guess (b) naming a new fruit photo (c) the learned patterns (d) recorded spoken words
  12. 12.True or false: “the learned patterns” is training data. (a) True (b) False
  13. 13.True or false: “the trained program” is the model. (a) False (b) True
  14. 14.⏩ 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
  15. 15.True or false: “labelled fruit photos” is training data. (a) False (b) True
  16. 16.Which of these is training data? (a) typing a new spoken word (b) what training builds (c) past weather records (d) flagging a new email
  17. 17.True or false: “what training builds” is training data. (a) True (b) False
  18. 18.Which of these is training data? (a) naming a new leaf (b) flagging a new email (c) what training builds (d) labelled fruit photos
  19. 19.⏩ In machine learning, which comes first: naming a new leaf or recorded spoken words? (a) naming a new leaf (b) recorded spoken words
  20. 20.True or false: “flagging a new email” is the model. (a) False (b) True
  21. 21.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) training data (c) a prediction
  22. 22.True or false: “naming a new fruit photo” is a prediction. (a) False (b) True
  23. 23.⏩ In machine learning, which comes first: recorded spoken words or flagging a new email? (a) recorded spoken words (b) flagging a new email
  24. 24.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  25. 25.⏩ In machine learning, which comes first: what training builds or naming a new fruit photo? (a) what training builds (b) naming a new fruit photo
  26. 26.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
  27. 27.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
  28. 28.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) a prediction (c) training data
  29. 29.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  30. 30.⏩ In machine learning, which comes first: flagging a new email or the trained program? (a) flagging a new email (b) the trained program
  31. 31.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  32. 32.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, prediction, model (d) data, model, prediction
  33. 33.True or false: “typing a new spoken word” is training data. (a) False (b) True
  34. 34.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) the model (c) training data
  35. 35.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) training data (c) a prediction
  36. 36.Which of these is training data? (a) old emails marked spam (b) naming a new leaf (c) the learned patterns (d) tomorrow’s rain guess
  37. 37.True or false: “past weather records” is training data. (a) False (b) True
  38. 38.⏩ In machine learning, which comes first: past weather records or what training builds? (a) past weather records (b) what training builds
  39. 39.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  40. 40.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model

Answer key

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

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