Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 407 · 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 good for training a model? (a) very few examples (b) testing on training data (c) labels added at random (d) photos in many lights
2. 2.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
3. 3.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) clean screens (d) print pages
4. 4.📚 Good or bad for training a model: wrong labels? (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? “Science project groups are on the board” (a) not spam (b) spam
6. 6.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
7. 7.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
8. 8.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
9. 9.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
10. 10.🥭 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 be perfect (d) it will shut down
11. 11.🔍 Which is the odd one out? (a) new data for testing (b) labels added at random (c) very few examples (d) wrong labels
12. 12.True or false: “many varied examples” is bad for training a model. (a) False (b) True
13. 13.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
14. 14.🔍 Which is the odd one out? (a) blurry, unclear photos (b) checking labels twice (c) many varied examples (d) clear, sharp examples
15. 15.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
16. 16.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the price (d) the right answer tag
17. 17.🔍 Which is the odd one out? (a) blurry, unclear photos (b) very few examples (c) only one kind of example (d) checking labels twice
18. 18.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
19. 19.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) new data for testing (d) testing on training data
20. 20.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
21. 21.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
22. 22.🔍 Which is the odd one out? (a) wrong labels (b) clear, sharp examples (c) examples of every type (d) correct labels
23. 23.True or false: “correct labels” is good for training a model. (a) True (b) False
24. 24.🔍 Which is the odd one out? (a) wrong labels (b) blurry, unclear photos (c) clear, sharp examples (d) only one kind of example
25. 25.Which of these is good for training a model? (a) examples of every type (b) very few examples (c) copies of one photo (d) only one kind of example
26. 26.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
27. 27.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
28. 28.Which of these is bad for training a model? (a) clear, sharp examples (b) checking labels twice (c) only one kind of example (d) correct labels
29. 29.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
30. 30.Which of these is good for training a model? (a) copies of one photo (b) very few examples (c) only one kind of example (d) checking labels twice
31. 31.🏷️ 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
32. 32.🔍 Which is the odd one out? (a) clear, sharp examples (b) labels added at random (c) many varied examples (d) examples of every type
33. 33.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
34. 34.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) copies of one photo (d) checking labels twice
35. 35.🔍 Which is the odd one out? (a) very few examples (b) copies of one photo (c) correct labels (d) testing on training data
36. 36.🏷️ 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
37. 37.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
38. 38.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
39. 39.Which of these is bad for training a model? (a) photos in many lights (b) copies of one photo (c) many varied examples (d) examples of every type
40. 40.Which of these is good for training a model? (a) testing on training data (b) many varied examples (c) copies of one photo (d) wrong labels

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