Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 463 · 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 is the odd one out? (a) clear, sharp examples (b) testing on training data (c) new data for testing (d) many varied examples
2. 2.True or false: “many varied examples” is good for training a model. (a) True (b) False
3. 3.Which of these is bad for training a model? (a) examples of every type (b) correct labels (c) checking labels twice (d) very few examples
4. 4.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
5. 5.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
6. 6.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) learn from data (d) print pages
7. 7.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
8. 8.🏷️ 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
9. 9.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
10. 10.Which of these is good for training a model? (a) wrong labels (b) testing on training data (c) very few examples (d) correct labels
11. 11.Which of these is bad for training a model? (a) photos in many lights (b) labels added at random (c) checking labels twice (d) correct labels
12. 12.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
13. 13.🏷️ 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
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.Which of these is good for training a model? (a) only one kind of example (b) wrong labels (c) clear, sharp examples (d) blurry, unclear photos
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam
17. 17.🏷️ What is a “label” in machine learning? (a) the price (b) the right answer tag (c) the font size (d) a sticker on a laptop
18. 18.🔍 Which is the odd one out? (a) many varied examples (b) new data for testing (c) very few examples (d) photos in many lights
19. 19.🔍 Which is the odd one out? (a) clear, sharp examples (b) copies of one photo (c) only one kind of example (d) blurry, unclear photos
20. 20.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) blurry, unclear photos (d) examples of every type
21. 21.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
22. 22.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
23. 23.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) slower to switch on (d) better at its task
24. 24.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
25. 25.True or false: “examples of every type” is bad for training a model. (a) True (b) False
26. 26.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
27. 27.True or false: “testing on training data” is bad for training a model. (a) False (b) True
28. 28.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
29. 29.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
30. 30.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
31. 31.Which of these is bad for training a model? (a) correct labels (b) clear, sharp examples (c) photos in many lights (d) testing on training data
32. 32.🏷️ 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) not spam (b) spam
33. 33.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
34. 34.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
35. 35.Which of these is good for training a model? (a) examples of every type (b) very few examples (c) labels added at random (d) copies of one photo
36. 36.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) checking labels twice (d) very few examples
37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
38. 38.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it may get it wrong (c) it will turn yellow (d) it will shut down
39. 39.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
40. 40.🔍 Which is the odd one out? (a) wrong labels (b) copies of one photo (c) photos in many lights (d) labels added at random

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