Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 469 · 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? “You won a free phone! Click now!” (a) not spam (b) spam
2. 2.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
3. 3.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it may get it wrong (d) it will turn yellow
4. 4.Which of these is good for training a model? (a) labels added at random (b) copies of one photo (c) very few examples (d) new data for testing
5. 5.🏷️ 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
6. 6.True or false: “only one kind of example” is good for training a model. (a) True (b) False
7. 7.True or false: “testing on training data” is bad for training a model. (a) True (b) False
8. 8.🏷️ 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
9. 9.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
10. 10.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
11. 11.True or false: the message “Last chance! Free gift card inside” should be labelled “not 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? “Send your password to claim a prize” (a) not spam (b) spam
14. 14.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) photos in many lights (d) very few examples
15. 15.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) learn from data (d) print pages
16. 16.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) many varied examples (d) very few examples
17. 17.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
18. 18.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
19. 19.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the right answer tag (d) the price
20. 20.Which of these is good for training a model? (a) blurry, unclear photos (b) copies of one photo (c) checking labels twice (d) wrong labels
21. 21.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
22. 22.🏷️ 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
23. 23.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
24. 24.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
25. 25.🔍 Which is the odd one out? (a) new data for testing (b) clear, sharp examples (c) examples of every type (d) testing on training data
26. 26.Which of these is good for training a model? (a) blurry, unclear photos (b) photos in many lights (c) wrong labels (d) testing on training data
27. 27.True or false: “copies of one photo” is good for training a model. (a) True (b) False
28. 28.True or false: “labels added at random” is good for training a model. (a) True (b) False
29. 29.Which of these is bad for training a model? (a) checking labels twice (b) photos in many lights (c) blurry, unclear photos (d) correct labels
30. 30.Which of these is bad for training a model? (a) new data for testing (b) testing on training data (c) clear, sharp examples (d) checking labels twice
31. 31.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
32. 32.Which of these is bad for training a model? (a) checking labels twice (b) very few examples (c) correct labels (d) clear, sharp examples
33. 33.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) forget everything (d) change colour
34. 34.🔍 Which is the odd one out? (a) wrong labels (b) checking labels twice (c) labels added at random (d) copies of one photo
35. 35.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
36. 36.Which of these is bad for training a model? (a) only one kind of example (b) clear, sharp examples (c) checking labels twice (d) correct labels
37. 37.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) one single photo (d) a list of rules only
38. 38.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
39. 39.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) labels added at random (d) correct labels
40. 40.🏷️ 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

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