Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 426 · 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: “correct labels” is bad for training a model. (a) True (b) False
2. 2.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
3. 3.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
4. 4.🔍 Which is the odd one out? (a) correct labels (b) examples of every type (c) checking labels twice (d) very few examples
5. 5.🏷️ 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
6. 6.Which of these is bad for training a model? (a) photos in many lights (b) examples of every type (c) many varied examples (d) very few examples
7. 7.🔍 Which is the odd one out? (a) blurry, unclear photos (b) new data for testing (c) correct labels (d) clear, sharp examples
8. 8.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
10. 10.Which of these is bad for training a model? (a) many varied examples (b) new data for testing (c) wrong labels (d) checking labels twice
11. 11.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
12. 12.True or false: “checking labels twice” is good for training a model. (a) False (b) True
13. 13.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) learn from data (d) print pages
14. 14.🏷️ 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
15. 15.🏷️ 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
16. 16.🔍 Which is the odd one out? (a) many varied examples (b) labels added at random (c) checking labels twice (d) new data for testing
17. 17.True or false: “testing on training data” is good for training a model. (a) True (b) False
18. 18.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
19. 19.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) checking labels twice (d) wrong labels
20. 20.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
21. 21.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
22. 22.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
23. 23.Which of these is good for training a model? (a) labels added at random (b) wrong labels (c) copies of one photo (d) correct labels
24. 24.🔍 Which is the odd one out? (a) many varied examples (b) examples of every type (c) only one kind of example (d) photos in many lights
25. 25.🔍 Which is the odd one out? (a) many varied examples (b) copies of one photo (c) blurry, unclear photos (d) very few examples
26. 26.Which of these is good for training a model? (a) very few examples (b) testing on training data (c) labels added at random (d) many varied examples
27. 27.🔍 Which is the odd one out? (a) labels added at random (b) copies of one photo (c) blurry, unclear photos (d) new data for testing
28. 28.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) False (b) True
29. 29.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) forget everything (d) better at its task
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
31. 31.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
32. 32.🥭 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
33. 33.Which of these is bad for training a model? (a) checking labels twice (b) new data for testing (c) correct labels (d) copies of one photo
34. 34.Which of these is bad for training a model? (a) many varied examples (b) correct labels (c) testing on training data (d) clear, sharp examples
35. 35.True or false: “correct labels” is good for training a model. (a) False (b) True
36. 36.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
37. 37.Which of these is good for training a model? (a) testing on training data (b) only one kind of example (c) photos in many lights (d) labels added at random
38. 38.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
39. 39.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
40. 40.🐶 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

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