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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 463 · 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 a prediction? (a) old emails marked spam (b) past weather records (c) what training builds (d) flagging a new email
  2. 2.🔁 What is the right order? (a) model, prediction, data (b) data, model, prediction (c) prediction, data, model (d) data, prediction, model
  3. 3.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to see if it works (d) to change its name
  4. 4.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a label error (c) a prediction (d) a password
  5. 5.Which of these is training data? (a) the learned patterns (b) the trained program (c) past weather records (d) what training builds
  6. 6.⏩ In machine learning, which comes first: 500 labelled leaf photos or the learned patterns? (a) 500 labelled leaf photos (b) the learned patterns
  7. 7.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) a prediction (c) the model
  8. 8.Which of these is training data? (a) the learned patterns (b) labelled fruit photos (c) the trained program (d) typing a new spoken word
  9. 9.📦 What happens during training? (a) it charges up (b) it prints labels (c) it learns patterns (d) it takes photos
  10. 10.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) a prediction (c) the model
  11. 11.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) the model (c) training data
  12. 12.Which of these is a prediction? (a) what training builds (b) typing a new spoken word (c) 500 labelled leaf photos (d) the trained program
  13. 13.True or false: “what training builds” is training data. (a) True (b) False
  14. 14.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  15. 15.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  16. 16.True or false: “typing a new spoken word” is the model. (a) True (b) False
  17. 17.True or false: “what training builds” is the model. (a) False (b) True
  18. 18.Which of these is a prediction? (a) past weather records (b) labelled fruit photos (c) tomorrow’s rain guess (d) what training builds
  19. 19.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) a prediction (c) training data
  20. 20.⏩ In machine learning, which comes first: what training builds or old emails marked spam? (a) what training builds (b) old emails marked spam
  21. 21.True or false: “flagging a new email” is training data. (a) True (b) False
  22. 22.True or false: “naming a new leaf” is training data. (a) False (b) True
  23. 23.Which of these is the model? (a) tomorrow’s rain guess (b) past weather records (c) naming a new leaf (d) the trained program
  24. 24.True or false: “the learned patterns” is training data. (a) True (b) False
  25. 25.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
  26. 26.⏩ In machine learning, which comes first: recorded spoken words or the learned patterns? (a) recorded spoken words (b) the learned patterns
  27. 27.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) training data (c) a prediction
  28. 28.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
  29. 29.Which of these is training data? (a) the learned patterns (b) tomorrow’s rain guess (c) recorded spoken words (d) the trained program
  30. 30.Which of these is training data? (a) the learned patterns (b) naming a new fruit photo (c) tomorrow’s rain guess (d) 500 labelled leaf photos
  31. 31.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  32. 32.⏩ In machine learning, which comes first: the trained program or recorded spoken words? (a) the trained program (b) recorded spoken words
  33. 33.Which of these is a prediction? (a) recorded spoken words (b) the trained program (c) labelled fruit photos (d) naming a new fruit photo
  34. 34.Which of these is training data? (a) tomorrow’s rain guess (b) old emails marked spam (c) the trained program (d) naming a new leaf
  35. 35.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  36. 36.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  37. 37.True or false: “old emails marked spam” is a prediction. (a) True (b) False
  38. 38.True or false: “old emails marked spam” is training data. (a) False (b) True
  39. 39.⏩ 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
  40. 40.True or false: “the trained program” is training data. (a) True (b) False

Answer key

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

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