Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 268 · 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: clear, sharp examples? (a) bad for training (b) good for training
2. 2.Which of these is bad for training a model? (a) only one kind of example (b) correct labels (c) clear, sharp examples (d) many varied examples
3. 3.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
4. 4.🔍 Which is the odd one out? (a) new data for testing (b) photos in many lights (c) correct labels (d) very few examples
5. 5.🔍 Which is the odd one out? (a) blurry, unclear photos (b) wrong labels (c) new data for testing (d) labels added at random
6. 6.🏷️ 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
7. 7.📚 Usually, more good examples make a model… (a) slower to switch on (b) change colour (c) forget everything (d) better at its task
8. 8.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
9. 9.True or false: “new data for testing” is bad for training a model. (a) True (b) False
10. 10.Which of these is bad for training a model? (a) new data for testing (b) examples of every type (c) many varied examples (d) copies of one photo
11. 11.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
12. 12.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
13. 13.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) False (b) True
14. 14.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) the font size (c) a sticker on a laptop (d) the price
15. 15.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
16. 16.Which of these is good for training a model? (a) testing on training data (b) clear, sharp examples (c) wrong labels (d) labels added at random
17. 17.🧠 Machine learning is a way for computers to… (a) charge faster (b) print pages (c) clean screens (d) learn from data
18. 18.📚 Good or bad for training a model: labels added at random? (a) bad for training (b) good for training
19. 19.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
20. 20.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
21. 21.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
22. 22.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
23. 23.🔍 Which is the odd one out? (a) blurry, unclear photos (b) photos in many lights (c) copies of one photo (d) only one kind of example
24. 24.Which of these is bad for training a model? (a) examples of every type (b) new data for testing (c) very few examples (d) many varied examples
25. 25.🔍 Which is the odd one out? (a) blurry, unclear photos (b) very few examples (c) correct labels (d) wrong labels
26. 26.Which of these is good for training a model? (a) correct labels (b) only one kind of example (c) very few examples (d) wrong labels
27. 27.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it may get it wrong (c) it will be perfect (d) it will shut down
28. 28.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
29. 29.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a list of rules only (d) a song about dogs
30. 30.Which of these is good for training a model? (a) blurry, unclear photos (b) only one kind of example (c) checking labels twice (d) very few examples
31. 31.True or false: “photos in many lights” 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) very few examples (c) clear, sharp examples (d) testing on training data
33. 33.🔍 Which is the odd one out? (a) new data for testing (b) examples of every type (c) many varied examples (d) copies of one photo
34. 34.Which of these is good for training a model? (a) blurry, unclear photos (b) very few examples (c) testing on training data (d) photos in many lights
35. 35.True or false: “correct labels” is bad for training a model. (a) True (b) False
36. 36.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
37. 37.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
38. 38.True or false: “correct labels” is good for training a model. (a) False (b) True
39. 39.🏷️ 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
40. 40.Which of these is bad for training a model? (a) clear, sharp examples (b) photos in many lights (c) examples of every type (d) wrong labels

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