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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 151 · 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 training data? (a) recorded spoken words (b) naming a new leaf (c) the learned patterns (d) the trained program
  2. 2.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) training data (c) a prediction (d) a password
  3. 3.Which of these is training data? (a) 500 labelled leaf photos (b) flagging a new email (c) tomorrow’s rain guess (d) the trained program
  4. 4.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) a prediction (c) the model
  5. 5.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) the model (c) training data
  6. 6.True or false: “past weather records” is the model. (a) True (b) False
  7. 7.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  8. 8.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  9. 9.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it takes photos (d) it prints labels
  10. 10.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  11. 11.⏩ In machine learning, which comes first: old emails marked spam or the learned patterns? (a) old emails marked spam (b) the learned patterns
  12. 12.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) the model (c) a prediction
  13. 13.Which of these is a prediction? (a) flagging a new email (b) past weather records (c) old emails marked spam (d) recorded spoken words
  14. 14.Which of these is training data? (a) old emails marked spam (b) the trained program (c) naming a new fruit photo (d) flagging a new email
  15. 15.Which of these is a prediction? (a) recorded spoken words (b) labelled fruit photos (c) what training builds (d) naming a new leaf
  16. 16.Which of these is training data? (a) naming a new leaf (b) the trained program (c) typing a new spoken word (d) past weather records
  17. 17.🧪 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
  18. 18.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  19. 19.🔁 What is the right order? (a) prediction, data, model (b) data, prediction, model (c) model, prediction, data (d) data, model, prediction
  20. 20.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  21. 21.⏩ 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
  22. 22.🔁 Training data, the model or a prediction: “past weather records”? (a) the model (b) a prediction (c) training data
  23. 23.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
  24. 24.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  25. 25.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) the model (c) training data
  26. 26.⏩ In machine learning, which comes first: labelled fruit photos or what training builds? (a) labelled fruit photos (b) what training builds
  27. 27.⏩ In machine learning, which comes first: recorded spoken words or tomorrow’s rain guess? (a) recorded spoken words (b) tomorrow’s rain guess
  28. 28.True or false: “old emails marked spam” is the model. (a) True (b) False
  29. 29.⏩ In machine learning, which comes first: past weather records or tomorrow’s rain guess? (a) past weather records (b) tomorrow’s rain guess
  30. 30.True or false: “recorded spoken words” is a prediction. (a) False (b) True
  31. 31.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  32. 32.⏩ In machine learning, which comes first: the learned patterns or past weather records? (a) the learned patterns (b) past weather records
  33. 33.⏩ 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
  34. 34.Which of these is the model? (a) past weather records (b) labelled fruit photos (c) old emails marked spam (d) the trained program
  35. 35.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  36. 36.True or false: “recorded spoken words” is the model. (a) False (b) True
  37. 37.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) the model (c) training data
  38. 38.⏩ In machine learning, which comes first: what training builds or past weather records? (a) what training builds (b) past weather records
  39. 39.⏩ In machine learning, which comes first: recorded spoken words or the trained program? (a) recorded spoken words (b) the trained program
  40. 40.Which of these is the model? (a) flagging a new email (b) naming a new fruit photo (c) old emails marked spam (d) the learned patterns

Answer key

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

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