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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 642 · 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.⏩ In machine learning, which comes first: naming a new leaf or old emails marked spam? (a) naming a new leaf (b) old emails marked spam
  2. 2.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) the model (c) a prediction
  3. 3.True or false: “recorded spoken words” is the model. (a) True (b) False
  4. 4.True or false: “tomorrow’s rain guess” is a prediction. (a) False (b) True
  5. 5.⏩ In machine learning, which comes first: tomorrow’s rain guess or the trained program? (a) tomorrow’s rain guess (b) the trained program
  6. 6.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) a prediction (c) the model
  7. 7.True or false: “labelled fruit photos” is training data. (a) False (b) True
  8. 8.Which of these is a prediction? (a) labelled fruit photos (b) recorded spoken words (c) flagging a new email (d) the trained program
  9. 9.⏩ In machine learning, which comes first: typing a new spoken word or what training builds? (a) typing a new spoken word (b) what training builds
  10. 10.True or false: “500 labelled leaf photos” is the model. (a) False (b) True
  11. 11.🧪 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
  12. 12.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  13. 13.True or false: “what training builds” is the model. (a) True (b) False
  14. 14.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
  15. 15.⏩ In machine learning, which comes first: recorded spoken words or naming a new leaf? (a) recorded spoken words (b) naming a new leaf
  16. 16.Which of these is training data? (a) the learned patterns (b) the trained program (c) what training builds (d) old emails marked spam
  17. 17.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, prediction, model (d) data, model, prediction
  18. 18.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
  19. 19.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  20. 20.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
  21. 21.⏩ 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
  22. 22.Which of these is training data? (a) what training builds (b) the learned patterns (c) typing a new spoken word (d) past weather records
  23. 23.⏩ In machine learning, which comes first: old emails marked spam or tomorrow’s rain guess? (a) old emails marked spam (b) tomorrow’s rain guess
  24. 24.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) training data (c) a prediction
  25. 25.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
  26. 26.⏩ In machine learning, which comes first: 500 labelled leaf photos or the learned patterns? (a) 500 labelled leaf photos (b) the learned patterns
  27. 27.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  28. 28.Which of these is the model? (a) past weather records (b) the learned patterns (c) labelled fruit photos (d) typing a new spoken word
  29. 29.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it prints labels (d) it takes photos
  30. 30.True or false: “naming a new leaf” is the model. (a) True (b) False
  31. 31.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) the model (c) a prediction
  32. 32.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  33. 33.Which of these is a prediction? (a) recorded spoken words (b) 500 labelled leaf photos (c) the learned patterns (d) naming a new leaf
  34. 34.Which of these is the model? (a) recorded spoken words (b) the trained program (c) naming a new fruit photo (d) past weather records
  35. 35.⏩ In machine learning, which comes first: typing a new spoken word or the learned patterns? (a) typing a new spoken word (b) the learned patterns
  36. 36.Which of these is a prediction? (a) what training builds (b) 500 labelled leaf photos (c) the trained program (d) tomorrow’s rain guess
  37. 37.⏩ In machine learning, which comes first: typing a new spoken word or the trained program? (a) typing a new spoken word (b) the trained program
  38. 38.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a label error (c) a password (d) training data
  39. 39.True or false: “the trained program” is the model. (a) False (b) True
  40. 40.True or false: “past weather records” is training data. (a) True (b) False

Answer key

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

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