Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 350 · 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 of these is bad for training a model? (a) new data for testing (b) photos in many lights (c) testing on training data (d) correct labels
2. 2.True or false: “testing on training data” is bad for training a model. (a) False (b) True
3. 3.🔍 Which is the odd one out? (a) labels added at random (b) new data for testing (c) blurry, unclear photos (d) wrong labels
4. 4.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
5. 5.🔍 Which is the odd one out? (a) copies of one photo (b) checking labels twice (c) many varied examples (d) new data for testing
6. 6.Which of these is good for training a model? (a) only one kind of example (b) correct labels (c) very few examples (d) blurry, unclear photos
7. 7.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) spam
8. 8.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) clear, sharp examples (d) labels added at random
9. 9.Which of these is bad for training a model? (a) many varied examples (b) very few examples (c) examples of every type (d) correct labels
10. 10.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
11. 11.True or false: “very few examples” is good for training a model. (a) False (b) True
12. 12.True or false: “checking labels twice” is bad for training a model. (a) True (b) False
13. 13.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
14. 14.Which of these is good for training a model? (a) many varied examples (b) blurry, unclear photos (c) only one kind of example (d) testing on training data
15. 15.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) True (b) False
16. 16.True or false: “new data for testing” is good for training a model. (a) False (b) True
17. 17.True or false: “correct labels” is bad for training a model. (a) False (b) True
18. 18.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
19. 19.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
20. 20.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
21. 21.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
22. 22.🏷️ What is a “label” in machine learning? (a) the right answer tag (b) a sticker on a laptop (c) the price (d) the font size
23. 23.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) print pages (d) learn from data
24. 24.🔍 Which is the odd one out? (a) correct labels (b) wrong labels (c) testing on training data (d) very few examples
25. 25.🔍 Which is the odd one out? (a) only one kind of example (b) labels added at random (c) very few examples (d) clear, sharp examples
26. 26.🥭 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
27. 27.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
28. 28.🔍 Which is the odd one out? (a) very few examples (b) examples of every type (c) blurry, unclear photos (d) only one kind of example
29. 29.🏷️ 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
30. 30.🔍 Which is the odd one out? (a) wrong labels (b) very few examples (c) checking labels twice (d) labels added at random
31. 31.🏷️ 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
32. 32.True or false: “new data for testing” is bad for training a model. (a) False (b) True
33. 33.🏷️ 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
34. 34.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
35. 35.🏷️ 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
36. 36.🔍 Which is the odd one out? (a) new data for testing (b) photos in many lights (c) blurry, unclear photos (d) examples of every type
37. 37.Which of these is bad for training a model? (a) new data for testing (b) copies of one photo (c) examples of every type (d) many varied examples
38. 38.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
39. 39.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) False (b) True
40. 40.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training

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