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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 815 · 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.📦 What happens during training? (a) it takes photos (b) it learns patterns (c) it prints labels (d) it charges up
  2. 2.True or false: “labelled fruit photos” is training data. (a) True (b) False
  3. 3.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) training data (c) a prediction
  4. 4.🔁 What is the right order? (a) prediction, data, model (b) model, prediction, data (c) data, prediction, model (d) data, model, prediction
  5. 5.True or false: “typing a new spoken word” is training data. (a) False (b) True
  6. 6.Which of these is the model? (a) naming a new leaf (b) the learned patterns (c) tomorrow’s rain guess (d) typing a new spoken word
  7. 7.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) a prediction (b) the model (c) training data
  8. 8.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) the model (c) a prediction
  9. 9.True or false: “naming a new leaf” is a prediction. (a) False (b) True
  10. 10.Which of these is a prediction? (a) recorded spoken words (b) typing a new spoken word (c) old emails marked spam (d) the trained program
  11. 11.⏩ In machine learning, which comes first: flagging a new email or past weather records? (a) flagging a new email (b) past weather records
  12. 12.True or false: “recorded spoken words” is training data. (a) False (b) True
  13. 13.🔁 Training data, the model or a prediction: “past weather records”? (a) a prediction (b) the model (c) training data
  14. 14.True or false: “past weather records” is the model. (a) False (b) True
  15. 15.🔁 Training data, the model or a prediction: “the learned patterns”? (a) the model (b) a prediction (c) training data
  16. 16.True or false: “old emails marked spam” is a prediction. (a) True (b) False
  17. 17.⏩ In machine learning, which comes first: flagging a new email or recorded spoken words? (a) flagging a new email (b) recorded spoken words
  18. 18.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
  19. 19.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) training data (b) the model (c) a prediction
  20. 20.True or false: “flagging a new email” is a prediction. (a) True (b) False
  21. 21.Which of these is training data? (a) typing a new spoken word (b) labelled fruit photos (c) the trained program (d) naming a new leaf
  22. 22.⏩ In machine learning, which comes first: the learned patterns or old emails marked spam? (a) the learned patterns (b) old emails marked spam
  23. 23.Which of these is the model? (a) naming a new fruit photo (b) old emails marked spam (c) what training builds (d) typing a new spoken word
  24. 24.🧪 Why test a model on NEW examples? (a) to delete its data (b) to see if it works (c) to make it slower (d) to change its name
  25. 25.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  26. 26.True or false: “500 labelled leaf photos” is the model. (a) True (b) False
  27. 27.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  28. 28.⏩ In machine learning, which comes first: what training builds or old emails marked spam? (a) what training builds (b) old emails marked spam
  29. 29.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) a password (c) a label error (d) training data
  30. 30.⏩ 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
  31. 31.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) a prediction (c) the model
  32. 32.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) a prediction (c) the model
  33. 33.⏩ In machine learning, which comes first: what training builds or flagging a new email? (a) what training builds (b) flagging a new email
  34. 34.Which of these is the model? (a) the trained program (b) naming a new leaf (c) recorded spoken words (d) naming a new fruit photo
  35. 35.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) training data (c) the model
  36. 36.Which of these is training data? (a) flagging a new email (b) typing a new spoken word (c) old emails marked spam (d) the trained program
  37. 37.True or false: “past weather records” is a prediction. (a) True (b) False
  38. 38.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) the model (b) a prediction (c) training data
  39. 39.True or false: “the learned patterns” is training data. (a) True (b) False
  40. 40.True or false: “typing a new spoken word” is a prediction. (a) False (b) True

Answer key

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

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