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AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 376 · 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 is the right order? (a) data, model, prediction (b) model, prediction, data (c) data, prediction, model (d) prediction, data, model
  2. 2.⏩ In machine learning, which comes first: the learned patterns or naming a new leaf? (a) the learned patterns (b) naming a new leaf
  3. 3.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) a prediction (c) training data
  4. 4.Which of these is the model? (a) the learned patterns (b) recorded spoken words (c) typing a new spoken word (d) 500 labelled leaf photos
  5. 5.⏩ 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
  6. 6.🔁 Training data, the model or a prediction: “tomorrow’s rain guess”? (a) training data (b) the model (c) a prediction
  7. 7.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  8. 8.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) the model (c) training data
  9. 9.Which of these is a prediction? (a) labelled fruit photos (b) what training builds (c) past weather records (d) naming a new leaf
  10. 10.Which of these is a prediction? (a) what training builds (b) old emails marked spam (c) the learned patterns (d) naming a new fruit photo
  11. 11.🧪 Why test a model on NEW examples? (a) to make it slower (b) to change its name (c) to delete its data (d) to see if it works
  12. 12.True or false: “recorded spoken words” is training data. (a) True (b) False
  13. 13.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) the model (c) a prediction
  14. 14.🔁 Training data, the model or a prediction: “flagging a new email”? (a) a prediction (b) the model (c) training data
  15. 15.🔮 A trained model sees a new photo and says “mango”. This is… (a) a password (b) training data (c) a label error (d) a prediction
  16. 16.⏩ In machine learning, which comes first: past weather records or the trained program? (a) past weather records (b) the trained program
  17. 17.True or false: “labelled fruit photos” is training data. (a) False (b) True
  18. 18.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) a prediction (b) the model (c) training data
  19. 19.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) training data (b) a prediction (c) the model
  20. 20.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) a prediction (b) the model (c) training data
  21. 21.⏩ In machine learning, which comes first: the learned patterns or tomorrow’s rain guess? (a) the learned patterns (b) tomorrow’s rain guess
  22. 22.⏩ In machine learning, which comes first: the trained program or 500 labelled leaf photos? (a) the trained program (b) 500 labelled leaf photos
  23. 23.True or false: “recorded spoken words” is a prediction. (a) True (b) False
  24. 24.🔁 Training data, the model or a prediction: “what training builds”? (a) training data (b) the model (c) a prediction
  25. 25.🔁 Training data, the model or a prediction: “the learned patterns”? (a) a prediction (b) training data (c) the model
  26. 26.Which of these is the model? (a) typing a new spoken word (b) past weather records (c) what training builds (d) 500 labelled leaf photos
  27. 27.⏩ In machine learning, which comes first: flagging a new email or the learned patterns? (a) flagging a new email (b) the learned patterns
  28. 28.⏩ In machine learning, which comes first: naming a new fruit photo or the learned patterns? (a) naming a new fruit photo (b) the learned patterns
  29. 29.📦 What happens during training? (a) it takes photos (b) it prints labels (c) it charges up (d) it learns patterns
  30. 30.True or false: “what training builds” is a prediction. (a) True (b) False
  31. 31.True or false: “typing a new spoken word” is training data. (a) True (b) False
  32. 32.⏩ In machine learning, which comes first: the trained program or tomorrow’s rain guess? (a) the trained program (b) tomorrow’s rain guess
  33. 33.True or false: “typing a new spoken word” is a prediction. (a) False (b) True
  34. 34.True or false: “the trained program” is training data. (a) False (b) True
  35. 35.True or false: “old emails marked spam” is training data. (a) True (b) False
  36. 36.⏩ In machine learning, which comes first: naming a new leaf or what training builds? (a) naming a new leaf (b) what training builds
  37. 37.Which of these is training data? (a) the trained program (b) naming a new fruit photo (c) recorded spoken words (d) typing a new spoken word
  38. 38.Which of these is training data? (a) past weather records (b) the trained program (c) the learned patterns (d) flagging a new email
  39. 39.⏩ In machine learning, which comes first: naming a new leaf or old emails marked spam? (a) naming a new leaf (b) old emails marked spam
  40. 40.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns

Answer key

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

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