← Training data, model and prediction lesson New set →

AI Worksheet: Training Data, Model, Prediction

AI for students lesson 3: Training data, model and prediction · Set 653 · 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.True or false: “the learned patterns” is a prediction. (a) False (b) True
  2. 2.⏩ In machine learning, which comes first: old emails marked spam or naming a new fruit photo? (a) old emails marked spam (b) naming a new fruit photo
  3. 3.⏩ In machine learning, which comes first: typing a new spoken word or the trained program? (a) typing a new spoken word (b) the trained program
  4. 4.True or false: “500 labelled leaf photos” is training data. (a) True (b) False
  5. 5.🔁 What is the right order? (a) data, prediction, model (b) data, model, prediction (c) model, prediction, data (d) prediction, data, model
  6. 6.Which of these is training data? (a) tomorrow’s rain guess (b) naming a new leaf (c) naming a new fruit photo (d) old emails marked spam
  7. 7.Which of these is a prediction? (a) labelled fruit photos (b) what training builds (c) typing a new spoken word (d) recorded spoken words
  8. 8.⏩ In machine learning, which comes first: labelled fruit photos or naming a new fruit photo? (a) labelled fruit photos (b) naming a new fruit photo
  9. 9.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) the model (c) a prediction
  10. 10.⏩ In machine learning, which comes first: labelled fruit photos or naming a new leaf? (a) labelled fruit photos (b) naming a new leaf
  11. 11.🧪 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
  12. 12.Which of these is training data? (a) naming a new fruit photo (b) the trained program (c) the learned patterns (d) past weather records
  13. 13.True or false: “past weather records” is the model. (a) False (b) True
  14. 14.⏩ In machine learning, which comes first: the learned patterns or old emails marked spam? (a) the learned patterns (b) old emails marked spam
  15. 15.🔁 Training data, the model or a prediction: “typing a new spoken word”? (a) training data (b) a prediction (c) the model
  16. 16.⏩ In machine learning, which comes first: 500 labelled leaf photos or what training builds? (a) 500 labelled leaf photos (b) what training builds
  17. 17.Which of these is the model? (a) past weather records (b) naming a new leaf (c) what training builds (d) 500 labelled leaf photos
  18. 18.⏩ In machine learning, which comes first: naming a new leaf or the learned patterns? (a) naming a new leaf (b) the learned patterns
  19. 19.⏩ In machine learning, which comes first: flagging a new email or what training builds? (a) flagging a new email (b) what training builds
  20. 20.Which of these is a prediction? (a) recorded spoken words (b) old emails marked spam (c) 500 labelled leaf photos (d) naming a new leaf
  21. 21.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) the model (b) training data (c) a prediction
  22. 22.Which of these is training data? (a) naming a new leaf (b) labelled fruit photos (c) tomorrow’s rain guess (d) the trained program
  23. 23.True or false: “tomorrow’s rain guess” is the model. (a) True (b) False
  24. 24.True or false: “recorded spoken words” is training data. (a) False (b) True
  25. 25.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) a prediction (c) training data
  26. 26.⏩ In machine learning, which comes first: naming a new fruit photo or labelled fruit photos? (a) naming a new fruit photo (b) labelled fruit photos
  27. 27.⏩ In machine learning, which comes first: what training builds or naming a new leaf? (a) what training builds (b) naming a new leaf
  28. 28.🔮 A trained model sees a new photo and says “mango”. This is… (a) training data (b) a prediction (c) a password (d) a label error
  29. 29.⏩ In machine learning, which comes first: typing a new spoken word or old emails marked spam? (a) typing a new spoken word (b) old emails marked spam
  30. 30.True or false: “the trained program” is the model. (a) False (b) True
  31. 31.⏩ In machine learning, which comes first: the trained program or naming a new leaf? (a) the trained program (b) naming a new leaf
  32. 32.Which of these is the model? (a) old emails marked spam (b) labelled fruit photos (c) the trained program (d) past weather records
  33. 33.True or false: “recorded spoken words” is a prediction. (a) False (b) True
  34. 34.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
  35. 35.True or false: “the trained program” is a prediction. (a) False (b) True
  36. 36.Which of these is training data? (a) flagging a new email (b) 500 labelled leaf photos (c) tomorrow’s rain guess (d) typing a new spoken word
  37. 37.🔁 Training data, the model or a prediction: “the learned patterns”? (a) training data (b) the model (c) a prediction
  38. 38.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) training data (b) a prediction (c) the model
  39. 39.True or false: “naming a new fruit photo” is a prediction. (a) True (b) False
  40. 40.True or false: “typing a new spoken word” is a prediction. (a) False (b) True

Answer key

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

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students