Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 291 · 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: checking labels twice? (a) bad for training (b) good for training
2. 2.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
3. 3.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) forget everything (d) change colour
4. 4.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) copies of one photo (d) photos in many lights
5. 5.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) a list of rules only (c) one single photo (d) many labelled photos
6. 6.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) checking labels twice (d) blurry, unclear photos
7. 7.True or false: “only one kind of example” is good for training a model. (a) False (b) True
8. 8.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
9. 9.🏷️ 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
10. 10.Which of these is good for training a model? (a) clear, sharp examples (b) labels added at random (c) blurry, unclear photos (d) wrong labels
11. 11.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
12. 12.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
13. 13.🔍 Which is the odd one out? (a) many varied examples (b) wrong labels (c) only one kind of example (d) blurry, unclear photos
14. 14.Which of these is bad for training a model? (a) checking labels twice (b) very few examples (c) correct labels (d) examples of every type
15. 15.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
17. 17.🔍 Which is the odd one out? (a) photos in many lights (b) checking labels twice (c) correct labels (d) very few examples
18. 18.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) photos in many lights (d) labels added at random
19. 19.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
20. 20.🔍 Which is the odd one out? (a) wrong labels (b) correct labels (c) clear, sharp examples (d) checking labels twice
21. 21.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
22. 22.Which of these is bad for training a model? (a) checking labels twice (b) clear, sharp examples (c) wrong labels (d) examples of every type
23. 23.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
24. 24.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
25. 25.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
26. 26.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
27. 27.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
28. 28.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
29. 29.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
30. 30.🔍 Which is the odd one out? (a) very few examples (b) clear, sharp examples (c) labels added at random (d) copies of one photo
31. 31.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
32. 32.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
33. 33.🏷️ 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
34. 34.🔍 Which is the odd one out? (a) correct labels (b) clear, sharp examples (c) checking labels twice (d) testing on training data
35. 35.🏷️ 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
36. 36.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
37. 37.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
38. 38.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
39. 39.Which of these is good for training a model? (a) wrong labels (b) testing on training data (c) correct labels (d) very few examples
40. 40.True or false: “labels added at random” is good for training a model. (a) True (b) False

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