Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 248 · 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 account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
2. 2.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
3. 3.Which of these is good for training a model? (a) wrong labels (b) testing on training data (c) copies of one photo (d) many varied examples
4. 4.🏷️ 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
5. 5.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a song about dogs (d) a list of rules only
6. 6.Which of these is bad for training a model? (a) checking labels twice (b) clear, sharp examples (c) copies of one photo (d) new data for testing
7. 7.Which of these is bad for training a model? (a) clear, sharp examples (b) checking labels twice (c) blurry, unclear photos (d) new data for testing
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) not spam (b) spam
9. 9.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) better at its task (d) slower to switch on
10. 10.🏷️ What is a “label” in machine learning? (a) the price (b) a sticker on a laptop (c) the font size (d) the right answer tag
11. 11.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will turn yellow (c) it will be perfect (d) it will shut down
12. 12.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
13. 13.🏷️ 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
14. 14.Which of these is bad for training a model? (a) photos in many lights (b) many varied examples (c) wrong labels (d) checking labels twice
15. 15.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
16. 16.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
17. 17.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
18. 18.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) charge faster (d) print pages
19. 19.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
21. 21.🔍 Which is the odd one out? (a) blurry, unclear photos (b) only one kind of example (c) clear, sharp examples (d) testing on training data
22. 22.Which of these is good for training a model? (a) copies of one photo (b) very few examples (c) photos in many lights (d) only one kind of example
23. 23.True or false: “examples of every type” is good for training a model. (a) False (b) True
24. 24.🔍 Which is the odd one out? (a) wrong labels (b) correct labels (c) blurry, unclear photos (d) copies of one photo
25. 25.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
26. 26.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) examples of every type (d) very few examples
27. 27.True or false: “many varied examples” is good for training a model. (a) False (b) True
28. 28.True or false: “only one kind of example” is good for training a model. (a) True (b) False
29. 29.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
30. 30.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
31. 31.Which of these is bad for training a model? (a) examples of every type (b) correct labels (c) clear, sharp examples (d) testing on training data
32. 32.True or false: “wrong labels” is bad for training a model. (a) True (b) False
33. 33.🔍 Which is the odd one out? (a) very few examples (b) photos in many lights (c) many varied examples (d) examples of every type
34. 34.Which of these is bad for training a model? (a) new data for testing (b) photos in many lights (c) only one kind of example (d) clear, sharp examples
35. 35.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
36. 36.True or false: “correct labels” is bad for training a model. (a) True (b) False
37. 37.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
38. 38.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
39. 39.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
40. 40.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False

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