Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 378 · 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 of these is bad for training a model? (a) examples of every type (b) checking labels twice (c) photos in many lights (d) only one kind of example
2. 2.Which of these is good for training a model? (a) photos in many lights (b) copies of one photo (c) labels added at random (d) blurry, unclear photos
3. 3.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
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.🏷️ 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
6. 6.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will shut down (c) it will be perfect (d) it will turn yellow
7. 7.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) print pages (d) learn from data
8. 8.🏷️ 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
9. 9.🔍 Which is the odd one out? (a) correct labels (b) labels added at random (c) blurry, unclear photos (d) wrong labels
10. 10.True or false: “examples of every type” is bad for training a model. (a) True (b) False
11. 11.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
12. 12.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
13. 13.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
14. 14.🏷️ 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
15. 15.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
16. 16.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) forget everything (d) change colour
17. 17.True or false: “photos in many lights” is bad 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? “Share your OTP to get cashback” (a) spam (b) not spam
19. 19.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
20. 20.True or false: “labels added at random” is bad for training a model. (a) True (b) False
21. 21.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
22. 22.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
23. 23.True or false: “new data for testing” is bad for training a model. (a) False (b) True
24. 24.True or false: “labels added at random” is good for training a model. (a) False (b) True
25. 25.True or false: “new data for testing” is good for training a model. (a) False (b) True
26. 26.True or false: “many varied examples” is bad for training a model. (a) True (b) False
27. 27.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the price (d) the font size
28. 28.Which of these is good for training a model? (a) checking labels twice (b) very few examples (c) labels added at random (d) testing on training data
29. 29.Which of these is bad for training a model? (a) correct labels (b) photos in many lights (c) clear, sharp examples (d) very few examples
30. 30.Which of these is good for training a model? (a) new data for testing (b) labels added at random (c) wrong labels (d) only one kind of example
31. 31.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
32. 32.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
33. 33.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
34. 34.Which of these is bad for training a model? (a) photos in many lights (b) checking labels twice (c) wrong labels (d) correct labels
35. 35.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
36. 36.🔍 Which is the odd one out? (a) very few examples (b) copies of one photo (c) many varied examples (d) only one kind of example
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 “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
39. 39.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) photos in many lights (d) copies of one photo
40. 40.🏷️ 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

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