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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 767 · 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.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  2. 2.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) the model (c) training data
  3. 3.True or false: “tomorrow’s rain guess” is a prediction. (a) True (b) False
  4. 4.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  5. 5.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  6. 6.⏩ In machine learning, which comes first: 500 labelled leaf photos or the learned patterns? (a) 500 labelled leaf photos (b) the learned patterns
  7. 7.⏩ In machine learning, which comes first: labelled fruit photos or the trained program? (a) labelled fruit photos (b) the trained program
  8. 8.Which of these is the model? (a) the learned patterns (b) recorded spoken words (c) naming a new fruit photo (d) flagging a new email
  9. 9.📦 What happens during training? (a) it learns patterns (b) it charges up (c) it takes photos (d) it prints labels
  10. 10.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to delete its data (d) to change its name
  11. 11.🔮 A trained model sees a new photo and says “mango”. This is… (a) a label error (b) a password (c) a prediction (d) training data
  12. 12.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
  13. 13.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  14. 14.Which of these is a prediction? (a) recorded spoken words (b) the trained program (c) typing a new spoken word (d) 500 labelled leaf photos
  15. 15.Which of these is training data? (a) flagging a new email (b) recorded spoken words (c) the learned patterns (d) naming a new leaf
  16. 16.⏩ In machine learning, which comes first: recorded spoken words or flagging a new email? (a) recorded spoken words (b) flagging a new email
  17. 17.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  18. 18.Which of these is the model? (a) the trained program (b) old emails marked spam (c) recorded spoken words (d) labelled fruit photos
  19. 19.⏩ In machine learning, which comes first: the trained program or old emails marked spam? (a) the trained program (b) old emails marked spam
  20. 20.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) a prediction (c) the model
  21. 21.Which of these is training data? (a) naming a new leaf (b) old emails marked spam (c) the learned patterns (d) flagging a new email
  22. 22.True or false: “flagging a new email” is training data. (a) False (b) True
  23. 23.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  24. 24.True or false: “recorded spoken words” is the model. (a) True (b) False
  25. 25.⏩ In machine learning, which comes first: 500 labelled leaf photos or flagging a new email? (a) 500 labelled leaf photos (b) flagging a new email
  26. 26.True or false: “past weather records” is a prediction. (a) False (b) True
  27. 27.True or false: “flagging a new email” is the model. (a) True (b) False
  28. 28.🔁 Training data, the model or a prediction: “the trained program”? (a) training data (b) a prediction (c) the model
  29. 29.True or false: “past weather records” is the model. (a) True (b) False
  30. 30.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) the model (c) a prediction
  31. 31.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  32. 32.⏩ In machine learning, which comes first: recorded spoken words or the learned patterns? (a) recorded spoken words (b) the learned patterns
  33. 33.True or false: “the learned patterns” is a prediction. (a) True (b) False
  34. 34.⏩ 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
  35. 35.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) the model (c) a prediction
  36. 36.True or false: “the learned patterns” is training data. (a) True (b) False
  37. 37.⏩ In machine learning, which comes first: old emails marked spam or what training builds? (a) old emails marked spam (b) what training builds
  38. 38.True or false: “naming a new leaf” is training data. (a) True (b) False
  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 recorded spoken words? (a) the learned patterns (b) recorded spoken words

Answer key

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

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