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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 932 · 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: what training builds or typing a new spoken word? (a) what training builds (b) typing a new spoken word
  2. 2.Which of these is the model? (a) flagging a new email (b) recorded spoken words (c) what training builds (d) naming a new leaf
  3. 3.⏩ 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
  4. 4.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) the model (c) a prediction
  5. 5.🔮 A trained model sees a new photo and says “mango”. This is… (a) a prediction (b) training data (c) a label error (d) a password
  6. 6.⏩ In machine learning, which comes first: 500 labelled leaf photos or the trained program? (a) 500 labelled leaf photos (b) the trained program
  7. 7.🧪 Why test a model on NEW examples? (a) to change its name (b) to see if it works (c) to delete its data (d) to make it slower
  8. 8.Which of these is training data? (a) recorded spoken words (b) tomorrow’s rain guess (c) naming a new leaf (d) flagging a new email
  9. 9.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  10. 10.📦 What happens during training? (a) it charges up (b) it learns patterns (c) it takes photos (d) it prints labels
  11. 11.⏩ In machine learning, which comes first: the learned patterns or old emails marked spam? (a) the learned patterns (b) old emails marked spam
  12. 12.Which of these is training data? (a) the learned patterns (b) what training builds (c) naming a new leaf (d) old emails marked spam
  13. 13.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) a prediction (b) training data (c) the model
  14. 14.🔁 What is the right order? (a) model, prediction, data (b) data, prediction, model (c) data, model, prediction (d) prediction, data, model
  15. 15.True or false: “the learned patterns” is a prediction. (a) True (b) False
  16. 16.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  17. 17.⏩ In machine learning, which comes first: the learned patterns or 500 labelled leaf photos? (a) the learned patterns (b) 500 labelled leaf photos
  18. 18.True or false: “tomorrow’s rain guess” is the model. (a) False (b) True
  19. 19.True or false: “typing a new spoken word” is training data. (a) False (b) True
  20. 20.Which of these is a prediction? (a) labelled fruit photos (b) old emails marked spam (c) recorded spoken words (d) flagging a new email
  21. 21.Which of these is a prediction? (a) the trained program (b) labelled fruit photos (c) naming a new leaf (d) 500 labelled leaf photos
  22. 22.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
  23. 23.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  24. 24.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) a prediction (c) training data
  25. 25.⏩ 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
  26. 26.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
  27. 27.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  28. 28.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  29. 29.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) training data (c) the model
  30. 30.True or false: “flagging a new email” is training data. (a) False (b) True
  31. 31.True or false: “what training builds” is the model. (a) False (b) True
  32. 32.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  33. 33.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) a prediction (b) training data (c) the model
  34. 34.True or false: “recorded spoken words” is training data. (a) False (b) True
  35. 35.True or false: “labelled fruit photos” is a prediction. (a) True (b) False
  36. 36.⏩ In machine learning, which comes first: the trained program or flagging a new email? (a) the trained program (b) flagging a new email
  37. 37.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) a prediction (c) training data
  38. 38.True or false: “the trained program” is training data. (a) False (b) True
  39. 39.True or false: “500 labelled leaf photos” is training data. (a) False (b) True
  40. 40.True or false: “past weather records” is the model. (a) True (b) False

Answer key

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

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