Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 578 · 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.🔍 Which is the odd one out? (a) wrong labels (b) correct labels (c) photos in many lights (d) many varied examples
2. 2.True or false: “testing on training data” is bad for training a model. (a) False (b) True
3. 3.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
4. 4.Which of these is good for training a model? (a) clear, sharp examples (b) labels added at random (c) very few examples (d) testing on training data
5. 5.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
6. 6.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
7. 7.True or false: “photos in many lights” is good for training a model. (a) False (b) True
8. 8.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True
9. 9.🔍 Which is the odd one out? (a) clear, sharp examples (b) examples of every type (c) new data for testing (d) only one kind of example
10. 10.🏷️ 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
11. 11.🔍 Which is the odd one out? (a) labels added at random (b) testing on training data (c) examples of every type (d) only one kind of example
12. 12.True or false: “wrong labels” is good for training a model. (a) True (b) False
13. 13.True or false: “testing on training data” is good for training a model. (a) True (b) False
14. 14.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) examples of every type (d) wrong labels
15. 15.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) print pages (d) learn from data
16. 16.True or false: “correct labels” is bad for training a model. (a) False (b) True
17. 17.🏷️ 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
18. 18.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
19. 19.True or false: “very few examples” is bad for training a model. (a) True (b) False
20. 20.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
21. 21.Which of these is good for training a model? (a) only one kind of example (b) examples of every type (c) wrong labels (d) very few examples
22. 22.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) new data for testing (d) blurry, unclear photos
23. 23.True or false: “labels added at random” is bad for training a model. (a) True (b) False
24. 24.🔍 Which is the odd one out? (a) very few examples (b) new data for testing (c) only one kind of example (d) testing on training data
25. 25.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) clear, sharp examples (d) testing on training data
26. 26.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
27. 27.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) False (b) True
28. 28.🏷️ 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
29. 29.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) slower to switch on (d) better at its task
30. 30.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
31. 31.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will be perfect (c) it may get it wrong (d) it will shut down
32. 32.🏷️ 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
33. 33.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
34. 34.Which of these is good for training a model? (a) blurry, unclear photos (b) only one kind of example (c) photos in many lights (d) very few examples
35. 35.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) the right answer tag (d) a sticker on a laptop
36. 36.🏷️ 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
37. 37.True or false: “correct labels” is good for training a model. (a) False (b) True
38. 38.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
39. 39.Which of these is bad for training a model? (a) only one kind of example (b) new data for testing (c) correct labels (d) photos in many lights
40. 40.🏷️ 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

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