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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 865 · 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 the model? (a) what training builds (b) typing a new spoken word (c) 500 labelled leaf photos (d) old emails marked spam
  2. 2.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  3. 3.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) training data (c) a prediction (d) a label error
  4. 4.🔁 What is the right order? (a) model, prediction, data (b) prediction, data, model (c) data, prediction, model (d) data, model, prediction
  5. 5.⏩ In machine learning, which comes first: the trained program or flagging a new email? (a) the trained program (b) flagging a new email
  6. 6.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
  7. 7.⏩ 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
  8. 8.Which of these is a prediction? (a) old emails marked spam (b) labelled fruit photos (c) what training builds (d) tomorrow’s rain guess
  9. 9.📦 What happens during training? (a) it charges up (b) it takes photos (c) it prints labels (d) it learns patterns
  10. 10.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  11. 11.Which of these is training data? (a) naming a new fruit photo (b) typing a new spoken word (c) the learned patterns (d) past weather records
  12. 12.True or false: “flagging a new email” is training data. (a) True (b) False
  13. 13.True or false: “what training builds” is training data. (a) True (b) False
  14. 14.True or false: “recorded spoken words” is a prediction. (a) False (b) True
  15. 15.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  16. 16.⏩ In machine learning, which comes first: the trained program or past weather records? (a) the trained program (b) past weather records
  17. 17.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
  18. 18.True or false: “tomorrow’s rain guess” is the model. (a) False (b) True
  19. 19.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) a prediction (c) the model
  20. 20.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to delete its data (d) to see if it works
  21. 21.⏩ In machine learning, which comes first: old emails marked spam or the trained program? (a) old emails marked spam (b) the trained program
  22. 22.Which of these is the model? (a) naming a new fruit photo (b) old emails marked spam (c) the trained program (d) past weather records
  23. 23.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  24. 24.Which of these is training data? (a) flagging a new email (b) typing a new spoken word (c) recorded spoken words (d) naming a new fruit photo
  25. 25.⏩ In machine learning, which comes first: recorded spoken words or tomorrow’s rain guess? (a) recorded spoken words (b) tomorrow’s rain guess
  26. 26.True or false: “past weather records” is training data. (a) False (b) True
  27. 27.⏩ In machine learning, which comes first: what training builds or recorded spoken words? (a) what training builds (b) recorded spoken words
  28. 28.Which of these is the model? (a) recorded spoken words (b) the learned patterns (c) past weather records (d) old emails marked spam
  29. 29.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) a prediction (c) the model
  30. 30.Which of these is a prediction? (a) old emails marked spam (b) typing a new spoken word (c) the trained program (d) past weather records
  31. 31.Which of these is a prediction? (a) past weather records (b) 500 labelled leaf photos (c) the trained program (d) flagging a new email
  32. 32.Which of these is training data? (a) the learned patterns (b) typing a new spoken word (c) old emails marked spam (d) the trained program
  33. 33.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  34. 34.True or false: “naming a new fruit photo” is a prediction. (a) False (b) True
  35. 35.True or false: “flagging a new email” is a prediction. (a) True (b) False
  36. 36.Which of these is a prediction? (a) the learned patterns (b) what training builds (c) the trained program (d) naming a new fruit photo
  37. 37.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  38. 38.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) the model (c) training data
  39. 39.True or false: “the trained program” is training data. (a) True (b) False
  40. 40.⏩ In machine learning, which comes first: the learned patterns or typing a new spoken word? (a) the learned patterns (b) typing a new spoken word

Answer key

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

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