Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 287 · 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? “The class picnic is on Friday at 8 am” (a) spam (b) not spam
2. 2.🔍 Which is the odd one out? (a) many varied examples (b) very few examples (c) new data for testing (d) correct labels
3. 3.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
4. 4.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) many labelled photos (d) a list of rules only
5. 5.🏷️ 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
6. 6.Which of these is bad for training a model? (a) photos in many lights (b) blurry, unclear photos (c) new data for testing (d) clear, sharp examples
7. 7.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
8. 8.True or false: “only one kind of example” is good for training a model. (a) False (b) True
9. 9.Which of these is good for training a model? (a) testing on training data (b) copies of one photo (c) many varied examples (d) labels added at random
10. 10.🔍 Which is the odd one out? (a) wrong labels (b) testing on training data (c) correct labels (d) labels added at random
11. 11.🏷️ 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
12. 12.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
13. 13.Which of these is bad for training a model? (a) many varied examples (b) checking labels twice (c) clear, sharp examples (d) testing on training data
14. 14.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
15. 15.True or false: “very few examples” is good for training a model. (a) True (b) False
16. 16.🔍 Which is the odd one out? (a) testing on training data (b) photos in many lights (c) very few examples (d) labels added at random
17. 17.Which of these is good for training a model? (a) testing on training data (b) very few examples (c) copies of one photo (d) new data for testing
18. 18.🔍 Which is the odd one out? (a) photos in many lights (b) new data for testing (c) many varied examples (d) blurry, unclear photos
19. 19.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
20. 20.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) photos in many lights (d) testing on training data
21. 21.🏷️ 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
22. 22.🏷️ 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
23. 23.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
24. 24.🧠 Machine learning is a way for computers to… (a) print pages (b) learn from data (c) clean screens (d) charge faster
25. 25.True or false: “new data for testing” is bad for training a model. (a) False (b) True
26. 26.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
27. 27.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
28. 28.Which of these is good for training a model? (a) checking labels twice (b) copies of one photo (c) blurry, unclear photos (d) labels added at random
29. 29.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
30. 30.🔍 Which is the odd one out? (a) many varied examples (b) wrong labels (c) only one kind of example (d) copies of one photo
31. 31.True or false: “labels added at random” is good for training a model. (a) False (b) True
32. 32.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
33. 33.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
34. 34.🔍 Which is the odd one out? (a) very few examples (b) blurry, unclear photos (c) clear, sharp examples (d) wrong labels
35. 35.🔍 Which is the odd one out? (a) wrong labels (b) checking labels twice (c) labels added at random (d) only one kind of example
36. 36.Which of these is bad for training a model? (a) clear, sharp examples (b) wrong labels (c) checking labels twice (d) many varied examples
37. 37.Which of these is bad for training a model? (a) many varied examples (b) examples of every type (c) correct labels (d) only one kind of example
38. 38.🏷️ 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
39. 39.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
40. 40.🏷️ 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

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