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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 583 · 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 a prediction? (a) what training builds (b) 500 labelled leaf photos (c) old emails marked spam (d) tomorrow’s rain guess
  2. 2.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a label error (c) a password (d) a prediction
  3. 3.Which of these is training data? (a) the learned patterns (b) old emails marked spam (c) naming a new fruit photo (d) typing a new spoken word
  4. 4.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
  5. 5.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
  6. 6.🧪 Why test a model on NEW examples? (a) to make it slower (b) to delete its data (c) to change its name (d) to see if it works
  7. 7.🔁 What is the right order? (a) model, prediction, data (b) prediction, data, model (c) data, model, prediction (d) data, prediction, model
  8. 8.⏩ In machine learning, which comes first: past weather records or typing a new spoken word? (a) past weather records (b) typing a new spoken word
  9. 9.True or false: “labelled fruit photos” is the model. (a) False (b) True
  10. 10.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  11. 11.True or false: “flagging a new email” is a prediction. (a) True (b) False
  12. 12.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  13. 13.🔁 Training data, the model or a prediction: “what training builds”? (a) the model (b) a prediction (c) training data
  14. 14.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
  15. 15.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) training data (b) the model (c) a prediction
  16. 16.Which of these is a prediction? (a) old emails marked spam (b) flagging a new email (c) the trained program (d) 500 labelled leaf photos
  17. 17.Which of these is the model? (a) recorded spoken words (b) the trained program (c) 500 labelled leaf photos (d) typing a new spoken word
  18. 18.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) the model (b) training data (c) a prediction
  19. 19.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  20. 20.⏩ In machine learning, which comes first: the learned patterns or naming a new fruit photo? (a) the learned patterns (b) naming a new fruit photo
  21. 21.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  22. 22.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False
  23. 23.Which of these is the model? (a) the learned patterns (b) tomorrow’s rain guess (c) labelled fruit photos (d) 500 labelled leaf photos
  24. 24.Which of these is a prediction? (a) the trained program (b) typing a new spoken word (c) labelled fruit photos (d) old emails marked spam
  25. 25.🔁 Training data, the model or a prediction: “the trained program”? (a) a prediction (b) training data (c) the model
  26. 26.⏩ In machine learning, which comes first: recorded spoken words or the learned patterns? (a) recorded spoken words (b) the learned patterns
  27. 27.⏩ In machine learning, which comes first: the learned patterns or old emails marked spam? (a) the learned patterns (b) old emails marked spam
  28. 28.📦 What happens during training? (a) it charges up (b) it prints labels (c) it learns patterns (d) it takes photos
  29. 29.Which of these is a prediction? (a) recorded spoken words (b) the learned patterns (c) labelled fruit photos (d) naming a new leaf
  30. 30.Which of these is training data? (a) the learned patterns (b) recorded spoken words (c) tomorrow’s rain guess (d) flagging a new email
  31. 31.Which of these is a prediction? (a) what training builds (b) the learned patterns (c) naming a new fruit photo (d) 500 labelled leaf photos
  32. 32.Which of these is training data? (a) the trained program (b) labelled fruit photos (c) tomorrow’s rain guess (d) typing a new spoken word
  33. 33.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) the model (c) training data
  34. 34.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  35. 35.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) a prediction (c) the model
  36. 36.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
  37. 37.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  38. 38.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  39. 39.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  40. 40.Which of these is training data? (a) what training builds (b) typing a new spoken word (c) 500 labelled leaf photos (d) flagging a new email

Answer key

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

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