Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 561 · 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? “Share your OTP to get cashback” (a) spam (b) not spam
2. 2.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
3. 3.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
4. 4.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
5. 5.🔍 Which is the odd one out? (a) copies of one photo (b) clear, sharp examples (c) testing on training data (d) very few examples
6. 6.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
7. 7.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) many varied examples (d) labels added at random
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) not spam (b) spam
9. 9.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
10. 10.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
11. 11.Which of these is good for training a model? (a) new data for testing (b) wrong labels (c) labels added at random (d) testing on training data
12. 12.Which of these is good for training a model? (a) blurry, unclear photos (b) clear, sharp examples (c) labels added at random (d) only one kind of example
13. 13.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
14. 14.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) only one kind of example (d) correct labels
15. 15.Which of these is good for training a model? (a) copies of one photo (b) photos in many lights (c) wrong labels (d) blurry, unclear photos
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
17. 17.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
18. 18.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
19. 19.🔍 Which is the odd one out? (a) copies of one photo (b) checking labels twice (c) clear, sharp examples (d) photos in many lights
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.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
22. 22.🏷️ 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
23. 23.🔍 Which is the odd one out? (a) testing on training data (b) checking labels twice (c) blurry, unclear photos (d) labels added at random
24. 24.True or false: “very few examples” is bad for training a model. (a) False (b) True
25. 25.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
26. 26.True or false: “many varied examples” is bad for training a model. (a) False (b) True
27. 27.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) the price (d) a sticker on a laptop
28. 28.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
29. 29.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
30. 30.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) slower to switch on (d) forget everything
31. 31.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) many labelled photos (d) a song about dogs
32. 32.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) blurry, unclear photos (d) many varied examples
33. 33.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
34. 34.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
35. 35.🔍 Which is the odd one out? (a) many varied examples (b) very few examples (c) correct labels (d) photos in many lights
36. 36.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
37. 37.Which of these is bad for training a model? (a) many varied examples (b) correct labels (c) copies of one photo (d) photos in many lights
38. 38.True or false: “wrong labels” is good for training a model. (a) True (b) False
39. 39.Which of these is bad for training a model? (a) many varied examples (b) correct labels (c) clear, sharp examples (d) very few examples
40. 40.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) blurry, unclear photos (d) new data for testing

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