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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 877 · 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.

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

Answer key

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

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