Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 345 · 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.🏷️ What is a “label” in machine learning? (a) the font size (b) the price (c) a sticker on a laptop (d) the right answer tag
2. 2.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
3. 3.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
4. 4.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) a list of rules only (d) one single photo
5. 5.🔍 Which is the odd one out? (a) correct labels (b) testing on training data (c) many varied examples (d) clear, sharp examples
6. 6.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
7. 7.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
8. 8.Which of these is good for training a model? (a) copies of one photo (b) photos in many lights (c) very few examples (d) only one kind of example
9. 9.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) learn from data (d) clean screens
10. 10.Which of these is good for training a model? (a) correct labels (b) blurry, unclear photos (c) copies of one photo (d) only one kind of example
11. 11.🔍 Which is the odd one out? (a) wrong labels (b) testing on training data (c) photos in many lights (d) blurry, unclear photos
12. 12.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) labels added at random (d) clear, sharp examples
13. 13.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
14. 14.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
15. 15.Which of these is bad for training a model? (a) very few examples (b) new data for testing (c) examples of every type (d) many varied examples
16. 16.True or false: “testing on training data” is bad for training a model. (a) True (b) False
17. 17.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
18. 18.Which of these is bad for training a model? (a) new data for testing (b) photos in many lights (c) clear, sharp examples (d) labels added at random
19. 19.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
20. 20.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
21. 21.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
22. 22.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
23. 23.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
24. 24.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
25. 25.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
26. 26.🔍 Which is the odd one out? (a) examples of every type (b) clear, sharp examples (c) correct labels (d) only one kind of example
27. 27.🏷️ 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
28. 28.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
29. 29.🏷️ 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
30. 30.True or false: “correct labels” is good for training a model. (a) False (b) True
31. 31.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
32. 32.Which of these is bad for training a model? (a) only one kind of example (b) many varied examples (c) clear, sharp examples (d) checking labels twice
33. 33.🔍 Which is the odd one out? (a) blurry, unclear photos (b) new data for testing (c) clear, sharp examples (d) correct labels
34. 34.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
35. 35.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
36. 36.🔍 Which is the odd one out? (a) copies of one photo (b) many varied examples (c) very few examples (d) labels added at random
37. 37.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
38. 38.🏷️ 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
39. 39.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
40. 40.🔍 Which is the odd one out? (a) photos in many lights (b) wrong labels (c) clear, sharp examples (d) correct labels

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