Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 436 · 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.🏷️ 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
2. 2.Which of these is good for training a model? (a) labels added at random (b) photos in many lights (c) wrong labels (d) very few examples
3. 3.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
4. 4.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) only one kind of example (d) correct labels
5. 5.Which of these is good for training a model? (a) only one kind of example (b) correct labels (c) blurry, unclear photos (d) very few examples
6. 6.🔍 Which is the odd one out? (a) only one kind of example (b) photos in many lights (c) copies of one photo (d) very few examples
7. 7.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
8. 8.🐶 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
9. 9.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
10. 10.True or false: “checking labels twice” is good for training a model. (a) False (b) True
11. 11.Which of these is bad for training a model? (a) clear, sharp examples (b) checking labels twice (c) examples of every type (d) wrong labels
12. 12.🔍 Which is the odd one out? (a) correct labels (b) photos in many lights (c) wrong labels (d) new data for testing
13. 13.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
14. 14.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) examples of every type (d) only one kind of example
15. 15.Which of these is bad for training a model? (a) photos in many lights (b) very few examples (c) new data for testing (d) examples of every type
16. 16.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
17. 17.True or false: “many varied examples” is bad for training a model. (a) True (b) False
18. 18.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
19. 19.🏷️ 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
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
21. 21.True or false: “wrong labels” is good for training a model. (a) True (b) False
22. 22.Which of these is good for training a model? (a) new data for testing (b) very few examples (c) labels added at random (d) copies of one photo
23. 23.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
24. 24.📚 Usually, more good examples make a model… (a) better at its task (b) forget everything (c) slower to switch on (d) change colour
25. 25.True or false: “blurry, unclear photos” is bad for training a model. (a) True (b) False
26. 26.🔍 Which is the odd one out? (a) copies of one photo (b) blurry, unclear photos (c) wrong labels (d) examples of every type
27. 27.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
28. 28.Which of these is good for training a model? (a) clear, sharp examples (b) only one kind of example (c) copies of one photo (d) wrong labels
29. 29.🔍 Which is the odd one out? (a) examples of every type (b) only one kind of example (c) photos in many lights (d) clear, sharp examples
30. 30.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
31. 31.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
32. 32.True or false: “labels added at random” is good for training a model. (a) False (b) True
33. 33.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
34. 34.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
35. 35.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
36. 36.🏷️ 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
37. 37.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
38. 38.True or false: “correct labels” is bad for training a model. (a) False (b) True
39. 39.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
40. 40.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training

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