Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 153 · 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 “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
2. 2.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the price (c) the font size (d) a sticker on a laptop
3. 3.🔍 Which is the odd one out? (a) photos in many lights (b) new data for testing (c) many varied examples (d) very few examples
4. 4.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
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) not spam (b) spam
6. 6.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
7. 7.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
8. 8.Which of these is good for training a model? (a) only one kind of example (b) many varied examples (c) labels added at random (d) wrong labels
9. 9.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
10. 10.Which of these is bad for training a model? (a) photos in many lights (b) checking labels twice (c) new data for testing (d) testing on training data
11. 11.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will be perfect (c) it may get it wrong (d) it will shut down
12. 12.🏷️ 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
13. 13.Which of these is bad for training a model? (a) copies of one photo (b) checking labels twice (c) correct labels (d) photos in many lights
14. 14.Which of these is good for training a model? (a) new data for testing (b) testing on training data (c) very few examples (d) copies of one photo
15. 15.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
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: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
18. 18.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
19. 19.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
20. 20.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
21. 21.True or false: “wrong labels” is good for training a model. (a) True (b) False
22. 22.🔍 Which is the odd one out? (a) testing on training data (b) wrong labels (c) clear, sharp examples (d) only one kind of example
23. 23.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
24. 24.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a list of rules only (c) a song about dogs (d) one single photo
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.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
27. 27.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
28. 28.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) clean screens (d) learn from data
29. 29.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
30. 30.🔍 Which is the odd one out? (a) correct labels (b) clear, sharp examples (c) testing on training data (d) new data for testing
31. 31.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
32. 32.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) better at its task (d) change colour
33. 33.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
34. 34.True or false: “photos in many lights” is good for training a model. (a) True (b) False
35. 35.Which of these is bad for training a model? (a) photos in many lights (b) clear, sharp examples (c) only one kind of example (d) many varied examples
36. 36.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
37. 37.True or false: “examples of every type” is good for training a model. (a) False (b) True
38. 38.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
39. 39.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
40. 40.🏷️ 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

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