Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 208 · 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.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) forget everything (d) change colour
2. 2.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) examples of every type (d) testing on training data
3. 3.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
4. 4.🔍 Which is the odd one out? (a) correct labels (b) very few examples (c) only one kind of example (d) labels added at random
5. 5.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the font size (d) the right answer tag
6. 6.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
7. 7.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) one single photo (d) a list of rules only
8. 8.True or false: “photos in many lights” is good for training a model. (a) False (b) True
9. 9.🏷️ 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
10. 10.🏷️ 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
11. 11.Which of these is good for training a model? (a) very few examples (b) photos in many lights (c) copies of one photo (d) testing on training data
12. 12.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will shut down (c) it will turn yellow (d) it may get it wrong
13. 13.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
14. 14.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
15. 15.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
16. 16.True or false: “labels added at random” is good 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) not spam (b) spam
18. 18.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
19. 19.True or false: “testing on training data” is good for training a model. (a) True (b) False
20. 20.Which of these is good for training a model? (a) testing on training data (b) labels added at random (c) correct labels (d) only one kind of example
21. 21.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
22. 22.Which of these is good for training a model? (a) wrong labels (b) labels added at random (c) only one kind of example (d) clear, sharp examples
23. 23.True or false: “only one kind of example” is good for training a model. (a) True (b) False
24. 24.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
25. 25.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
26. 26.Which of these is bad for training a model? (a) wrong labels (b) correct labels (c) examples of every type (d) checking labels twice
27. 27.🔍 Which is the odd one out? (a) very few examples (b) examples of every type (c) correct labels (d) checking labels twice
28. 28.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
29. 29.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
30. 30.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam
31. 31.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
32. 32.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
33. 33.🔍 Which is the odd one out? (a) very few examples (b) only one kind of example (c) clear, sharp examples (d) labels added at random
34. 34.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
35. 35.🔍 Which is the odd one out? (a) photos in many lights (b) new data for testing (c) labels added at random (d) correct labels
36. 36.True or false: “very few examples” is bad for training a model. (a) True (b) False
37. 37.🔍 Which is the odd one out? (a) clear, sharp examples (b) checking labels twice (c) photos in many lights (d) copies of one photo
38. 38.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) new data for testing (d) blurry, unclear photos
39. 39.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
40. 40.🏷️ 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

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