Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 417 · 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.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
2. 2.Which of these is good for training a model? (a) photos in many lights (b) blurry, unclear photos (c) copies of one photo (d) very few examples
3. 3.🏷️ What is a “label” in machine learning? (a) the price (b) the font size (c) a sticker on a laptop (d) the right answer tag
4. 4.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will turn yellow (c) it will be perfect (d) it will shut down
5. 5.🏷️ 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
6. 6.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
7. 7.Which of these is good for training a model? (a) new data for testing (b) only one kind of example (c) labels added at random (d) testing on training data
8. 8.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
9. 9.🔍 Which is the odd one out? (a) correct labels (b) only one kind of example (c) photos in many lights (d) checking labels twice
10. 10.🔍 Which is the odd one out? (a) examples of every type (b) blurry, unclear photos (c) new data for testing (d) clear, sharp examples
11. 11.Which of these is good for training a model? (a) testing on training data (b) labels added at random (c) blurry, unclear photos (d) correct labels
12. 12.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
13. 13.True or false: “examples of every type” is bad for training a model. (a) True (b) False
14. 14.Which of these is bad for training a model? (a) clear, sharp examples (b) copies of one photo (c) examples of every type (d) checking labels twice
15. 15.🏷️ 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
16. 16.🏷️ 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
17. 17.🔍 Which is the odd one out? (a) very few examples (b) wrong labels (c) only one kind of example (d) new data for testing
18. 18.🏷️ 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
19. 19.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) charge faster (d) print pages
20. 20.🏷️ 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
21. 21.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
22. 22.True or false: “photos in many lights” is bad for training a model. (a) True (b) False
23. 23.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
24. 24.True or false: “many varied examples” is bad for training a model. (a) True (b) False
25. 25.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
26. 26.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
27. 27.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
28. 28.🔍 Which is the odd one out? (a) many varied examples (b) labels added at random (c) wrong labels (d) copies of one photo
29. 29.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
30. 30.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) clear, sharp examples (d) very few examples
31. 31.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) forget everything (d) better at its task
32. 32.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
33. 33.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
34. 34.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
35. 35.🔍 Which is the odd one out? (a) many varied examples (b) wrong labels (c) checking labels twice (d) correct labels
36. 36.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
37. 37.True or false: “examples of every type” is good for training a model. (a) False (b) True
38. 38.True or false: “wrong labels” is bad for training a model. (a) False (b) True
39. 39.Which of these is bad for training a model? (a) checking labels twice (b) blurry, unclear photos (c) correct labels (d) new data for testing
40. 40.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True

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