← 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 570 · 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.Which of these is a prediction? (a) labelled fruit photos (b) past weather records (c) the learned patterns (d) typing a new spoken word
  3. 3.⏩ In machine learning, which comes first: typing a new spoken word or 500 labelled leaf photos? (a) typing a new spoken word (b) 500 labelled leaf photos
  4. 4.⏩ In machine learning, which comes first: recorded spoken words or what training builds? (a) recorded spoken words (b) what training builds
  5. 5.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) the model (b) a prediction (c) training data
  6. 6.🧪 Why test a model on NEW examples? (a) to change its name (b) to make it slower (c) to see if it works (d) to delete its data
  7. 7.🔁 Training data, the model or a prediction: “naming a new fruit photo”? (a) the model (b) a prediction (c) training data
  8. 8.🔁 Training data, the model or a prediction: “500 labelled leaf photos”? (a) the model (b) training data (c) a prediction
  9. 9.True or false: “recorded spoken words” is training data. (a) False (b) True
  10. 10.⏩ In machine learning, which comes first: the learned patterns or labelled fruit photos? (a) the learned patterns (b) labelled fruit photos
  11. 11.True or false: “naming a new fruit photo” is the model. (a) False (b) True
  12. 12.⏩ In machine learning, which comes first: naming a new leaf or the trained program? (a) naming a new leaf (b) the trained program
  13. 13.Which of these is training data? (a) naming a new leaf (b) the trained program (c) the learned patterns (d) old emails marked spam
  14. 14.⏩ In machine learning, which comes first: tomorrow’s rain guess or the learned patterns? (a) tomorrow’s rain guess (b) the learned patterns
  15. 15.True or false: “the trained program” is training data. (a) True (b) False
  16. 16.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  17. 17.⏩ In machine learning, which comes first: naming a new leaf or past weather records? (a) naming a new leaf (b) past weather records
  18. 18.True or false: “old emails marked spam” is training data. (a) False (b) True
  19. 19.True or false: “recorded spoken words” is a prediction. (a) True (b) False
  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) tomorrow’s rain guess (b) recorded spoken words (c) naming a new leaf (d) the learned patterns
  22. 22.⏩ In machine learning, which comes first: 500 labelled leaf photos or flagging a new email? (a) 500 labelled leaf photos (b) flagging a new email
  23. 23.⏩ In machine learning, which comes first: naming a new leaf or recorded spoken words? (a) naming a new leaf (b) recorded spoken words
  24. 24.True or false: “past weather records” is a prediction. (a) True (b) False
  25. 25.🔁 What is the right order? (a) prediction, data, model (b) data, model, prediction (c) model, prediction, data (d) data, prediction, model
  26. 26.Which of these is a prediction? (a) past weather records (b) naming a new leaf (c) old emails marked spam (d) 500 labelled leaf photos
  27. 27.🔁 Training data, the model or a prediction: “naming a new leaf”? (a) the model (b) training data (c) a prediction
  28. 28.Which of these is the model? (a) old emails marked spam (b) typing a new spoken word (c) what training builds (d) past weather records
  29. 29.True or false: “tomorrow’s rain guess” is training data. (a) False (b) True
  30. 30.Which of these is training data? (a) flagging a new email (b) naming a new leaf (c) the trained program (d) past weather records
  31. 31.🔁 Training data, the model or a prediction: “recorded spoken words”? (a) a prediction (b) the model (c) training data
  32. 32.Which of these is training data? (a) naming a new leaf (b) tomorrow’s rain guess (c) 500 labelled leaf photos (d) flagging a new email
  33. 33.⏩ In machine learning, which comes first: tomorrow’s rain guess or what training builds? (a) tomorrow’s rain guess (b) what training builds
  34. 34.🔁 Training data, the model or a prediction: “past weather records”? (a) training data (b) a prediction (c) the model
  35. 35.Which of these is the model? (a) 500 labelled leaf photos (b) tomorrow’s rain guess (c) the learned patterns (d) past weather records
  36. 36.🔮 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
  37. 37.Which of these is training data? (a) naming a new fruit photo (b) the trained program (c) labelled fruit photos (d) what training builds
  38. 38.True or false: “past weather records” is training data. (a) False (b) True
  39. 39.True or false: “old emails marked spam” is a prediction. (a) True (b) False
  40. 40.Which of these is a prediction? (a) old emails marked spam (b) 500 labelled leaf photos (c) past weather records (d) tomorrow’s rain guess

Answer key

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

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