Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 191 · 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.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
2. 2.🏷️ 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
3. 3.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
4. 4.🏷️ 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
5. 5.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
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 turn yellow (c) it will shut down (d) it will be perfect
7. 7.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
8. 8.True or false: “new data for testing” is bad for training a model. (a) True (b) False
9. 9.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
10. 10.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
11. 11.Which of these is good for training a model? (a) wrong labels (b) testing on training data (c) photos in many lights (d) only one kind of example
12. 12.Which of these is good for training a model? (a) labels added at random (b) very few examples (c) new data for testing (d) copies of one photo
13. 13.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
14. 14.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) a sticker on a laptop (d) the right answer tag
15. 15.True or false: “checking labels twice” is good for training a model. (a) False (b) True
16. 16.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
17. 17.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) clean screens (d) learn from data
18. 18.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
19. 19.🏷️ 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
20. 20.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) better at its task (d) forget everything
21. 21.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
22. 22.True or false: “correct labels” is bad for training a model. (a) True (b) False
23. 23.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
24. 24.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
25. 25.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
26. 26.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
27. 27.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
28. 28.🔍 Which is the odd one out? (a) very few examples (b) blurry, unclear photos (c) wrong labels (d) clear, sharp examples
29. 29.True or false: “examples of every type” is bad for training a model. (a) False (b) True
30. 30.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a list of rules only (c) one single photo (d) a song about dogs
31. 31.🔍 Which is the odd one out? (a) clear, sharp examples (b) correct labels (c) wrong labels (d) examples of every type
32. 32.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) only one kind of example (d) checking labels twice
33. 33.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
34. 34.🏷️ 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
35. 35.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
36. 36.Which of these is bad for training a model? (a) checking labels twice (b) examples of every type (c) very few examples (d) new data for testing
37. 37.🔍 Which is the odd one out? (a) copies of one photo (b) wrong labels (c) checking labels twice (d) labels added at random
38. 38.Which of these is bad for training a model? (a) blurry, unclear photos (b) examples of every type (c) checking labels twice (d) correct labels
39. 39.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
40. 40.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) correct labels (d) copies of one photo

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