Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 400 · 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.🏷️ 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
2. 2.🥭 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
3. 3.🏷️ 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
4. 4.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
5. 5.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) copies of one photo (d) new data for testing
6. 6.🏷️ 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
7. 7.True or false: “wrong labels” is bad for training a model. (a) False (b) True
8. 8.Which of these is good for training a model? (a) testing on training data (b) blurry, unclear photos (c) examples of every type (d) labels added at random
9. 9.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
10. 10.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
11. 11.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
12. 12.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
13. 13.🏷️ 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
14. 14.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
15. 15.🏷️ 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
16. 16.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
17. 17.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
18. 18.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
19. 19.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
20. 20.Which of these is bad for training a model? (a) photos in many lights (b) new data for testing (c) labels added at random (d) many varied examples
21. 21.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
22. 22.🔍 Which is the odd one out? (a) testing on training data (b) very few examples (c) examples of every type (d) labels added at random
23. 23.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
24. 24.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) print pages (d) clean screens
25. 25.🏷️ 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
26. 26.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
27. 27.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
28. 28.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
29. 29.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
30. 30.🔍 Which is the odd one out? (a) blurry, unclear photos (b) new data for testing (c) labels added at random (d) only one kind of example
31. 31.Which of these is good for training a model? (a) checking labels twice (b) only one kind of example (c) blurry, unclear photos (d) very few examples
32. 32.Which of these is bad for training a model? (a) examples of every type (b) testing on training data (c) photos in many lights (d) many varied examples
33. 33.🔍 Which is the odd one out? (a) labels added at random (b) copies of one photo (c) wrong labels (d) correct labels
34. 34.True or false: “new data for testing” is good for training a model. (a) False (b) True
35. 35.🏷️ 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
36. 36.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the right answer tag (d) the font size
37. 37.True or false: “only one kind of example” is good for training a model. (a) False (b) True
38. 38.Which of these is good for training a model? (a) labels added at random (b) wrong labels (c) copies of one photo (d) clear, sharp examples
39. 39.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
40. 40.🏷️ 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

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