Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 261 · 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: “labels added at random” is bad for training a model. (a) True (b) False
2. 2.🏷️ 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
3. 3.True or false: “copies of one photo” is good for training a model. (a) True (b) False
4. 4.Which of these is bad for training a model? (a) clear, sharp examples (b) new data for testing (c) correct labels (d) blurry, unclear photos
5. 5.🏷️ 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
6. 6.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
7. 7.🔍 Which is the odd one out? (a) photos in many lights (b) wrong labels (c) labels added at random (d) very few examples
8. 8.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) photos in many lights (d) labels added at random
9. 9.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
10. 10.Which of these is good for training a model? (a) copies of one photo (b) blurry, unclear photos (c) many varied examples (d) very few examples
11. 11.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
12. 12.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
13. 13.True or false: “copies of one photo” is bad for training a model. (a) True (b) False
14. 14.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
15. 15.🏷️ 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
16. 16.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
17. 17.🏷️ 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
18. 18.🏷️ 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
19. 19.🥭 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
20. 20.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
21. 21.True or false: “wrong labels” is bad for training a model. (a) False (b) True
22. 22.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) testing on training data (d) new data for testing
23. 23.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
24. 24.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
25. 25.Which of these is bad for training a model? (a) new data for testing (b) checking labels twice (c) wrong labels (d) clear, sharp examples
26. 26.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
27. 27.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) clean screens (d) learn from data
28. 28.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
29. 29.🔍 Which is the odd one out? (a) examples of every type (b) new data for testing (c) blurry, unclear photos (d) photos in many lights
30. 30.Which of these is good for training a model? (a) very few examples (b) examples of every type (c) wrong labels (d) only one kind of example
31. 31.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) only one kind of example (b) wrong labels (c) labels added at random (d) checking labels twice
33. 33.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
34. 34.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
35. 35.🔍 Which is the odd one out? (a) very few examples (b) checking labels twice (c) clear, sharp examples (d) new data for testing
36. 36.🔍 Which is the odd one out? (a) correct labels (b) only one kind of example (c) testing on training data (d) copies of one photo
37. 37.True or false: “labels added at random” is good for training a model. (a) False (b) True
38. 38.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
39. 39.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) change colour (d) better at its task
40. 40.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training

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