Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 122 · 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 “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
2. 2.🐶 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) one single photo (d) a song about dogs
3. 3.🔍 Which is the odd one out? (a) wrong labels (b) photos in many lights (c) correct labels (d) examples of every type
4. 4.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
5. 5.🔍 Which is the odd one out? (a) new data for testing (b) checking labels twice (c) blurry, unclear photos (d) photos in many lights
6. 6.Which of these is bad for training a model? (a) examples of every type (b) checking labels twice (c) wrong labels (d) correct labels
7. 7.True or false: “wrong labels” is bad for training a model. (a) False (b) True
8. 8.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
9. 9.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
10. 10.True or false: “very few examples” is bad for training a model. (a) True (b) False
11. 11.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) copies of one photo (d) correct labels
12. 12.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
13. 13.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it may get it wrong (c) it will shut down (d) it will be perfect
14. 14.🔍 Which is the odd one out? (a) photos in many lights (b) clear, sharp examples (c) only one kind of example (d) correct labels
15. 15.🏷️ 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
16. 16.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) print pages (d) learn from data
17. 17.True or false: “wrong labels” is good for training a model. (a) True (b) False
18. 18.🏷️ 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
19. 19.🔍 Which is the odd one out? (a) photos in many lights (b) clear, sharp examples (c) correct labels (d) copies of one photo
20. 20.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
21. 21.🏷️ 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
22. 22.Which of these is good for training a model? (a) blurry, unclear photos (b) very few examples (c) checking labels twice (d) testing on training data
23. 23.True or false: the message “Please buy milk on the way home” 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) not spam (b) spam
25. 25.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
26. 26.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
27. 27.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
28. 28.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) forget everything (d) better at its task
29. 29.🏷️ 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
30. 30.True or false: “many varied examples” is bad for training a model. (a) True (b) False
31. 31.True or false: “labels added at random” is good for training a model. (a) False (b) True
32. 32.Which of these is good for training a model? (a) photos in many lights (b) testing on training data (c) blurry, unclear photos (d) labels added at random
33. 33.True or false: “new data for testing” is bad for training a model. (a) True (b) False
34. 34.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) testing on training data (d) many varied examples
35. 35.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
36. 36.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
37. 37.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
38. 38.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
39. 39.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
40. 40.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training

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