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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 656 · 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: “past weather records”? (a) the model (b) training data (c) a prediction
  2. 2.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  3. 3.Which of these is the model? (a) old emails marked spam (b) recorded spoken words (c) 500 labelled leaf photos (d) the trained program
  4. 4.⏩ In machine learning, which comes first: naming a new leaf or recorded spoken words? (a) naming a new leaf (b) recorded spoken words
  5. 5.📦 What happens during training? (a) it learns patterns (b) it takes photos (c) it prints labels (d) it charges up
  6. 6.🔁 What is the right order? (a) data, prediction, model (b) prediction, data, model (c) data, model, prediction (d) model, prediction, data
  7. 7.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  8. 8.🔁 Training data, the model or a prediction: “flagging a new email”? (a) the model (b) training data (c) a prediction
  9. 9.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) a prediction (b) the model (c) training data
  10. 10.⏩ In machine learning, which comes first: typing a new spoken word or past weather records? (a) typing a new spoken word (b) past weather records
  11. 11.True or false: “what training builds” is the model. (a) False (b) True
  12. 12.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) a prediction (c) a label error (d) training data
  13. 13.⏩ In machine learning, which comes first: labelled fruit photos or what training builds? (a) labelled fruit photos (b) what training builds
  14. 14.True or false: “typing a new spoken word” is a prediction. (a) True (b) False
  15. 15.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) training data (b) the model (c) a prediction
  16. 16.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) the model (b) a prediction (c) training data
  17. 17.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
  18. 18.True or false: “what training builds” is training data. (a) False (b) True
  19. 19.🧪 Why test a model on NEW examples? (a) to make it slower (b) to delete its data (c) to see if it works (d) to change its name
  20. 20.Which of these is the model? (a) labelled fruit photos (b) the learned patterns (c) flagging a new email (d) naming a new fruit photo
  21. 21.Which of these is training data? (a) naming a new leaf (b) flagging a new email (c) recorded spoken words (d) what training builds
  22. 22.Which of these is a prediction? (a) tomorrow’s rain guess (b) past weather records (c) the learned patterns (d) the trained program
  23. 23.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  24. 24.🔁 Training data, the model or a prediction: “the trained program”? (a) the model (b) a prediction (c) training data
  25. 25.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  26. 26.True or false: “past weather records” is training data. (a) False (b) True
  27. 27.True or false: “naming a new leaf” is the model. (a) True (b) False
  28. 28.⏩ In machine learning, which comes first: tomorrow’s rain guess or 500 labelled leaf photos? (a) tomorrow’s rain guess (b) 500 labelled leaf photos
  29. 29.⏩ In machine learning, which comes first: the trained program or naming a new fruit photo? (a) the trained program (b) naming a new fruit photo
  30. 30.⏩ In machine learning, which comes first: tomorrow’s rain guess or past weather records? (a) tomorrow’s rain guess (b) past weather records
  31. 31.⏩ In machine learning, which comes first: what training builds or typing a new spoken word? (a) what training builds (b) typing a new spoken word
  32. 32.Which of these is training data? (a) old emails marked spam (b) naming a new fruit photo (c) the trained program (d) tomorrow’s rain guess
  33. 33.Which of these is a prediction? (a) the learned patterns (b) what training builds (c) flagging a new email (d) old emails marked spam
  34. 34.True or false: “flagging a new email” is the model. (a) False (b) True
  35. 35.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  36. 36.Which of these is a prediction? (a) the trained program (b) naming a new fruit photo (c) 500 labelled leaf photos (d) recorded spoken words
  37. 37.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  38. 38.⏩ In machine learning, which comes first: what training builds or labelled fruit photos? (a) what training builds (b) labelled fruit photos
  39. 39.True or false: “recorded spoken words” is training data. (a) True (b) False
  40. 40.Which of these is the model? (a) tomorrow’s rain guess (b) old emails marked spam (c) what training builds (d) typing a new spoken word

Answer key

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

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