Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 59 · 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.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
2. 2.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
3. 3.True or false: “testing on training data” is bad for training a model. (a) True (b) False
4. 4.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) many labelled photos (d) a list of rules only
5. 5.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
6. 6.Which of these is good for training a model? (a) new data for testing (b) labels added at random (c) copies of one photo (d) testing on training data
7. 7.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
8. 8.🔍 Which is the odd one out? (a) very few examples (b) new data for testing (c) testing on training data (d) labels added at random
9. 9.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
10. 10.🏷️ 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
11. 11.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
12. 12.🏷️ 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
13. 13.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
14. 14.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
15. 15.True or false: “wrong labels” is good for training a model. (a) False (b) True
16. 16.🔍 Which is the odd one out? (a) clear, sharp examples (b) wrong labels (c) blurry, unclear photos (d) testing on training data
17. 17.True or false: “examples of every type” is good for training a model. (a) False (b) True
18. 18.True or false: “labels added at random” is good for training a model. (a) True (b) False
19. 19.Which of these is bad for training a model? (a) correct labels (b) only one kind of example (c) clear, sharp examples (d) examples of every type
20. 20.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
21. 21.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
22. 22.🏷️ 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
23. 23.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
24. 24.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
25. 25.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
26. 26.Which of these is good for training a model? (a) copies of one photo (b) very few examples (c) checking labels twice (d) wrong labels
27. 27.🔍 Which is the odd one out? (a) clear, sharp examples (b) labels added at random (c) many varied examples (d) new data for testing
28. 28.🔍 Which is the odd one out? (a) clear, sharp examples (b) new data for testing (c) testing on training data (d) photos in many lights
29. 29.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
30. 30.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
31. 31.True or false: “checking labels twice” is good for training a model. (a) False (b) True
32. 32.🔍 Which is the odd one out? (a) copies of one photo (b) photos in many lights (c) clear, sharp examples (d) examples of every type
33. 33.Which of these is bad for training a model? (a) labels added at random (b) photos in many lights (c) clear, sharp examples (d) examples of every type
34. 34.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
35. 35.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
36. 36.Which of these is bad for training a model? (a) testing on training data (b) photos in many lights (c) checking labels twice (d) examples of every type
37. 37.🔍 Which is the odd one out? (a) correct labels (b) blurry, unclear photos (c) photos in many lights (d) new data for testing
38. 38.🏷️ 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
39. 39.🏷️ 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
40. 40.Which of these is good for training a model? (a) very few examples (b) many varied examples (c) only one kind of example (d) labels added at random

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