Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 119 · 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.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
2. 2.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
3. 3.🔍 Which is the odd one out? (a) testing on training data (b) blurry, unclear photos (c) only one kind of example (d) clear, sharp examples
4. 4.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) copies of one photo (d) correct labels
5. 5.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
6. 6.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
7. 7.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
8. 8.🔍 Which is the odd one out? (a) checking labels twice (b) new data for testing (c) very few examples (d) photos in many lights
9. 9.🔍 Which is the odd one out? (a) examples of every type (b) very few examples (c) copies of one photo (d) testing on training data
10. 10.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
11. 11.True or false: “many varied examples” is good for training a model. (a) False (b) True
12. 12.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
13. 13.🔍 Which is the odd one out? (a) copies of one photo (b) photos in many lights (c) very few examples (d) blurry, unclear photos
14. 14.Which of these is good for training a model? (a) photos in many lights (b) labels added at random (c) only one kind of example (d) testing on training data
15. 15.Which of these is bad for training a model? (a) photos in many lights (b) wrong labels (c) new data for testing (d) checking labels twice
16. 16.True or false: “examples of every type” is bad for training a model. (a) True (b) False
17. 17.Which of these is good for training a model? (a) wrong labels (b) very few examples (c) examples of every type (d) testing on training data
18. 18.True or false: “clear, sharp examples” is good for training a model. (a) True (b) False
19. 19.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
20. 20.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
21. 21.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will be perfect (c) it will turn yellow (d) it may get it wrong
22. 22.🔍 Which is the odd one out? (a) very few examples (b) wrong labels (c) only one kind of example (d) checking labels twice
23. 23.Which of these is good for training a model? (a) testing on training data (b) wrong labels (c) only one kind of example (d) correct labels
24. 24.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
25. 25.🏷️ 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
26. 26.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
27. 27.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
28. 28.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) charge faster (d) print pages
29. 29.Which of these is bad for training a model? (a) correct labels (b) copies of one photo (c) many varied examples (d) photos in many lights
30. 30.Which of these is bad for training a model? (a) many varied examples (b) new data for testing (c) very few examples (d) checking labels twice
31. 31.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
32. 32.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
33. 33.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
34. 34.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a song about dogs (d) a list of rules only
35. 35.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
36. 36.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
37. 37.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) examples of every type (d) blurry, unclear photos
38. 38.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
39. 39.🔍 Which is the odd one out? (a) correct labels (b) checking labels twice (c) testing on training data (d) many varied examples
40. 40.True or false: “copies of one photo” is good for training a model. (a) True (b) False

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