Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 270 · 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) new data for testing (b) labels added at random (c) correct labels (d) clear, sharp examples
2. 2.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
3. 3.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
4. 4.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
5. 5.Which of these is good for training a model? (a) copies of one photo (b) examples of every type (c) testing on training data (d) wrong labels
6. 6.True or false: “many varied examples” is bad for training a model. (a) True (b) False
7. 7.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) change colour (d) better at its task
8. 8.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
9. 9.Which of these is good for training a model? (a) correct labels (b) only one kind of example (c) very few examples (d) blurry, unclear photos
10. 10.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
11. 11.🧠 Machine learning is a way for computers to… (a) charge faster (b) clean screens (c) print pages (d) learn from data
12. 12.🏷️ What is a “label” in machine learning? (a) the font size (b) a sticker on a laptop (c) the right answer tag (d) the price
13. 13.Which of these is bad for training a model? (a) clear, sharp examples (b) testing on training data (c) examples of every type (d) correct labels
14. 14.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
15. 15.Which of these is bad for training a model? (a) blurry, unclear photos (b) new data for testing (c) photos in many lights (d) examples of every type
16. 16.🔍 Which is the odd one out? (a) many varied examples (b) only one kind of example (c) labels added at random (d) blurry, unclear photos
17. 17.Which of these is bad for training a model? (a) clear, sharp examples (b) only one kind of example (c) many varied examples (d) examples of every type
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.🔍 Which is the odd one out? (a) checking labels twice (b) copies of one photo (c) blurry, unclear photos (d) testing on training data
20. 20.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
21. 21.True or false: “examples of every type” is bad for training a model. (a) False (b) True
22. 22.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
23. 23.🔍 Which is the odd one out? (a) only one kind of example (b) photos in many lights (c) very few examples (d) wrong labels
24. 24.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) True (b) False
25. 25.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) True (b) False
26. 26.Which of these is good for training a model? (a) blurry, unclear photos (b) very few examples (c) wrong labels (d) clear, sharp examples
27. 27.🏷️ 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
28. 28.Which of these is good for training a model? (a) wrong labels (b) copies of one photo (c) only one kind of example (d) checking labels twice
29. 29.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
30. 30.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
31. 31.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
32. 32.Which of these is bad for training a model? (a) correct labels (b) new data for testing (c) wrong labels (d) many varied examples
33. 33.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
34. 34.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
35. 35.🏷️ 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
36. 36.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
38. 38.Which of these is bad for training a model? (a) copies of one photo (b) photos in many lights (c) checking labels twice (d) correct labels
39. 39.Which of these is bad for training a model? (a) checking labels twice (b) clear, sharp examples (c) labels added at random (d) photos in many lights
40. 40.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True

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