Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 144 · 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.🔍 Which is the odd one out? (a) wrong labels (b) blurry, unclear photos (c) very few examples (d) new data for testing
2. 2.🧠 Machine learning is a way for computers to… (a) learn from data (b) print pages (c) charge faster (d) clean screens
3. 3.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) one single photo (d) a list of rules only
4. 4.🏷️ 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
5. 5.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
6. 6.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
7. 7.Which of these is bad for training a model? (a) only one kind of example (b) new data for testing (c) examples of every type (d) many varied examples
8. 8.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
9. 9.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
10. 10.🔍 Which is the odd one out? (a) only one kind of example (b) labels added at random (c) copies of one photo (d) correct labels
11. 11.Which of these is good for training a model? (a) labels added at random (b) testing on training data (c) correct labels (d) wrong labels
12. 12.Which of these is good for training a model? (a) many varied examples (b) blurry, unclear photos (c) labels added at random (d) only one kind of example
13. 13.🏷️ 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
14. 14.🏷️ 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
15. 15.🔍 Which is the odd one out? (a) checking labels twice (b) photos in many lights (c) clear, sharp examples (d) blurry, unclear photos
16. 16.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
17. 17.Which of these is bad for training a model? (a) photos in many lights (b) checking labels twice (c) very few examples (d) examples of every type
18. 18.📚 Usually, more good examples make a model… (a) better at its task (b) change colour (c) forget everything (d) slower to switch on
19. 19.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
20. 20.🔍 Which is the odd one out? (a) checking labels twice (b) photos in many lights (c) correct labels (d) very few examples
21. 21.Which of these is bad for training a model? (a) many varied examples (b) correct labels (c) checking labels twice (d) wrong labels
22. 22.🏷️ 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
23. 23.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
24. 24.🏷️ 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
25. 25.True or false: “examples of every type” is good for training a model. (a) True (b) False
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.🏷️ 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.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
29. 29.Which of these is bad for training a model? (a) new data for testing (b) checking labels twice (c) blurry, unclear photos (d) examples of every type
30. 30.Which of these is good for training a model? (a) only one kind of example (b) blurry, unclear photos (c) examples of every type (d) very few examples
31. 31.🏷️ 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
32. 32.True or false: “examples of every type” is bad for training a model. (a) False (b) True
33. 33.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
34. 34.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
35. 35.True or false: “many varied examples” is bad for training a model. (a) False (b) True
36. 36.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
37. 37.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
38. 38.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
39. 39.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) blurry, unclear photos (d) photos in many lights
40. 40.🔍 Which is the odd one out? (a) examples of every type (b) wrong labels (c) new data for testing (d) correct labels

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