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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 913 · 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 a prediction. (a) True (b) False
  2. 2.🔁 What is the right order? (a) data, prediction, model (b) prediction, data, model (c) data, model, prediction (d) model, prediction, data
  3. 3.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
  4. 4.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  5. 5.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a password (c) training data (d) a prediction
  6. 6.Which of these is a prediction? (a) what training builds (b) 500 labelled leaf photos (c) flagging a new email (d) labelled fruit photos
  7. 7.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) the model (c) training data
  8. 8.⏩ In machine learning, which comes first: recorded spoken words or the learned patterns? (a) recorded spoken words (b) the learned patterns
  9. 9.Which of these is a prediction? (a) past weather records (b) typing a new spoken word (c) 500 labelled leaf photos (d) the learned patterns
  10. 10.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  11. 11.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  12. 12.🧪 Why test a model on NEW examples? (a) to delete its data (b) to make it slower (c) to change its name (d) to see if it works
  13. 13.Which of these is the model? (a) naming a new fruit photo (b) labelled fruit photos (c) the trained program (d) naming a new leaf
  14. 14.True or false: “past weather records” is a prediction. (a) False (b) True
  15. 15.📦 What happens during training? (a) it learns patterns (b) it takes photos (c) it prints labels (d) it charges up
  16. 16.Which of these is training data? (a) old emails marked spam (b) the trained program (c) tomorrow’s rain guess (d) the learned patterns
  17. 17.⏩ In machine learning, which comes first: what training builds or 500 labelled leaf photos? (a) what training builds (b) 500 labelled leaf photos
  18. 18.Which of these is a prediction? (a) 500 labelled leaf photos (b) past weather records (c) naming a new leaf (d) old emails marked spam
  19. 19.Which of these is training data? (a) tomorrow’s rain guess (b) naming a new leaf (c) typing a new spoken word (d) recorded spoken words
  20. 20.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  21. 21.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
  22. 22.⏩ In machine learning, which comes first: typing a new spoken word or past weather records? (a) typing a new spoken word (b) past weather records
  23. 23.Which of these is the model? (a) the learned patterns (b) past weather records (c) typing a new spoken word (d) flagging a new email
  24. 24.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  25. 25.Which of these is the model? (a) old emails marked spam (b) what training builds (c) tomorrow’s rain guess (d) labelled fruit photos
  26. 26.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  27. 27.Which of these is a prediction? (a) what training builds (b) recorded spoken words (c) tomorrow’s rain guess (d) old emails marked spam
  28. 28.True or false: “typing a new spoken word” is the model. (a) True (b) False
  29. 29.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) the model (c) a prediction
  30. 30.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
  31. 31.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) a prediction (c) training data
  32. 32.True or false: “recorded spoken words” is training data. (a) True (b) False
  33. 33.⏩ 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
  34. 34.⏩ 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
  35. 35.⏩ In machine learning, which comes first: naming a new fruit photo or recorded spoken words? (a) naming a new fruit photo (b) recorded spoken words
  36. 36.⏩ In machine learning, which comes first: the learned patterns or flagging a new email? (a) the learned patterns (b) flagging a new email
  37. 37.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  38. 38.True or false: “naming a new fruit photo” is training data. (a) False (b) True
  39. 39.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) training data (c) the model
  40. 40.Which of these is training data? (a) naming a new fruit photo (b) 500 labelled leaf photos (c) what training builds (d) the learned patterns

Answer key

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

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