Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 409 · 40 questions

AI tip (Show, label, learn): Machine learning learns patterns from many labelled examples — a label is the right answer tag on each example. Good for training: many varied examples, correct labels, every type the model will meet, and separate new data for testing. Bad for training: very few examples, wrong or random labels, only one kind of example, blurry examples, testing on the training data.

1. 1.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
2. 2.🔍 Which is the odd one out? (a) correct labels (b) photos in many lights (c) examples of every type (d) very few examples
3. 3.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
4. 4.True or false: “many varied examples” is bad for training a model. (a) False (b) True
5. 5.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
6. 6.🔍 Which is the odd one out? (a) clear, sharp examples (b) only one kind of example (c) examples of every type (d) correct labels
7. 7.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
9. 9.True or false: “many varied examples” is good for training a model. (a) True (b) False
10. 10.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
11. 11.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
12. 12.Which of these is bad for training a model? (a) new data for testing (b) clear, sharp examples (c) copies of one photo (d) photos in many lights
13. 13.True or false: “labels added at random” is bad for training a model. (a) True (b) False
14. 14.True or false: “copies of one photo” is good for training a model. (a) True (b) False
15. 15.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) better at its task (d) forget everything
16. 16.Which of these is good for training a model? (a) copies of one photo (b) photos in many lights (c) very few examples (d) blurry, unclear photos
17. 17.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) spam (b) not spam
18. 18.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will shut down (c) it may get it wrong (d) it will turn yellow
19. 19.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) a list of rules only (d) many labelled photos
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
21. 21.Which of these is bad for training a model? (a) correct labels (b) clear, sharp examples (c) new data for testing (d) blurry, unclear photos
22. 22.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
23. 23.Which of these is good for training a model? (a) new data for testing (b) very few examples (c) wrong labels (d) testing on training data
24. 24.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) correct labels (d) testing on training data
25. 25.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
26. 26.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
27. 27.Which of these is bad for training a model? (a) clear, sharp examples (b) labels added at random (c) correct labels (d) new data for testing
28. 28.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
29. 29.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
30. 30.Which of these is good for training a model? (a) blurry, unclear photos (b) correct labels (c) labels added at random (d) wrong labels
31. 31.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) copies of one photo (b) photos in many lights (c) many varied examples (d) checking labels twice
33. 33.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
34. 34.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
35. 35.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
36. 36.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
37. 37.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
38. 38.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
39. 39.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
40. 40.Which of these is good for training a model? (a) blurry, unclear photos (b) copies of one photo (c) examples of every type (d) testing on training data

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