Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 329 · 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.🧠 Machine learning is a way for computers to… (a) learn from data (b) charge faster (c) clean screens (d) print pages
2. 2.Which of these is bad for training a model? (a) photos in many lights (b) new data for testing (c) very few examples (d) checking labels twice
3. 3.True or false: “examples of every type” is bad for training a model. (a) False (b) True
4. 4.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will shut down (c) it will be perfect (d) it will turn yellow
5. 5.🏷️ 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
6. 6.🔍 Which is the odd one out? (a) examples of every type (b) only one kind of example (c) correct labels (d) many varied examples
7. 7.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
8. 8.🔍 Which is the odd one out? (a) clear, sharp examples (b) copies of one photo (c) many varied examples (d) examples of every type
9. 9.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
10. 10.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
11. 11.Which of these is bad for training a model? (a) examples of every type (b) labels added at random (c) new data for testing (d) correct labels
12. 12.Which of these is good for training a model? (a) only one kind of example (b) copies of one photo (c) photos in many lights (d) wrong labels
13. 13.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
14. 14.Which of these is good for training a model? (a) blurry, unclear photos (b) wrong labels (c) testing on training data (d) new data for testing
15. 15.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
16. 16.🐶 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
17. 17.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
18. 18.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
19. 19.Which of these is bad for training a model? (a) clear, sharp examples (b) new data for testing (c) checking labels twice (d) copies of one photo
20. 20.🔍 Which is the odd one out? (a) copies of one photo (b) clear, sharp examples (c) labels added at random (d) wrong labels
21. 21.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
22. 22.True or false: “wrong labels” is good for training a model. (a) False (b) True
23. 23.Which of these is good for training a model? (a) blurry, unclear photos (b) copies of one photo (c) examples of every type (d) only one kind of example
24. 24.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) correct labels (d) wrong labels
25. 25.🏷️ What is a “label” in machine learning? (a) the font size (b) the price (c) a sticker on a laptop (d) the right answer tag
26. 26.Which of these is good for training a model? (a) testing on training data (b) blurry, unclear photos (c) checking labels twice (d) only one kind of example
27. 27.Which of these is good for training a model? (a) blurry, unclear photos (b) correct labels (c) wrong labels (d) copies of one photo
28. 28.True or false: “wrong labels” is bad for training a model. (a) False (b) True
29. 29.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
30. 30.🏷️ 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
31. 31.🔍 Which is the odd one out? (a) testing on training data (b) many varied examples (c) photos in many lights (d) checking labels twice
32. 32.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
33. 33.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) checking labels twice (d) wrong labels
34. 34.Which of these is bad for training a model? (a) clear, sharp examples (b) checking labels twice (c) examples of every type (d) testing on training data
35. 35.True or false: “labels added at random” is good for training a model. (a) True (b) False
36. 36.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) spam (b) not spam
38. 38.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
39. 39.🏷️ 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
40. 40.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False

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