Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 84 · 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 “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
2. 2.True or false: “copies of one photo” is good for training a model. (a) False (b) True
3. 3.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
4. 4.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) labels added at random (d) examples of every type
5. 5.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
6. 6.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
7. 7.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
8. 8.Which of these is good for training a model? (a) testing on training data (b) labels added at random (c) wrong labels (d) correct labels
9. 9.Which of these is bad for training a model? (a) correct labels (b) wrong labels (c) many varied examples (d) new data for testing
10. 10.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
11. 11.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
12. 12.🔍 Which is the odd one out? (a) testing on training data (b) very few examples (c) only one kind of example (d) checking labels twice
13. 13.🔍 Which is the odd one out? (a) checking labels twice (b) clear, sharp examples (c) examples of every type (d) only one kind of example
14. 14.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a list of rules only (d) a song about dogs
15. 15.🏷️ 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
16. 16.🏷️ 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
17. 17.🏷️ 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
18. 18.True or false: “new data for testing” is bad for training a model. (a) False (b) True
19. 19.🧠 Machine learning is a way for computers to… (a) learn from data (b) print pages (c) charge faster (d) clean screens
20. 20.🔍 Which is the odd one out? (a) examples of every type (b) clear, sharp examples (c) checking labels twice (d) labels added at random
21. 21.True or false: “new data for testing” is good for training a model. (a) True (b) False
22. 22.Which of these is bad for training a model? (a) blurry, unclear photos (b) clear, sharp examples (c) many varied examples (d) new data for testing
23. 23.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
24. 24.🏷️ What is a “label” in machine learning? (a) the price (b) the right answer tag (c) a sticker on a laptop (d) the font size
25. 25.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
26. 26.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) photos in many lights (d) testing on training data
27. 27.Which of these is bad for training a model? (a) examples of every type (b) photos in many lights (c) correct labels (d) labels added at random
28. 28.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
29. 29.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
31. 31.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
32. 32.🔍 Which is the odd one out? (a) examples of every type (b) very few examples (c) wrong labels (d) testing on training data
33. 33.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
34. 34.Which of these is bad for training a model? (a) many varied examples (b) photos in many lights (c) very few examples (d) correct labels
35. 35.🔍 Which is the odd one out? (a) many varied examples (b) very few examples (c) clear, sharp examples (d) photos in many lights
36. 36.🏷️ 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
37. 37.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
38. 38.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) labels added at random (d) clear, sharp examples
39. 39.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
40. 40.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training

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