Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 595 · 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) correct labels (b) new data for testing (c) testing on training data (d) examples of every type
2. 2.True or false: “copies of one photo” is good for training a model. (a) False (b) True
3. 3.🏷️ 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
4. 4.True or false: “new data for testing” is good for training a model. (a) True (b) False
5. 5.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
6. 6.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
7. 7.🥭 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
8. 8.True or false: “many varied examples” is bad for training a model. (a) True (b) False
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
10. 10.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
11. 11.🔍 Which is the odd one out? (a) many varied examples (b) copies of one photo (c) photos in many lights (d) correct labels
12. 12.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
13. 13.Which of these is good for training a model? (a) checking labels twice (b) wrong labels (c) only one kind of example (d) very few examples
14. 14.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) True (b) False
15. 15.Which of these is bad for training a model? (a) correct labels (b) clear, sharp examples (c) labels added at random (d) photos in many lights
16. 16.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “The class picnic is on Friday at 8 am” (a) not spam (b) spam
17. 17.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the right answer tag (d) the price
18. 18.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
19. 19.🔍 Which is the odd one out? (a) very few examples (b) testing on training data (c) photos in many lights (d) labels added at random
20. 20.🧠 Machine learning is a way for computers to… (a) clean screens (b) print pages (c) charge faster (d) learn from data
21. 21.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) many labelled photos (c) a song about dogs (d) one single photo
22. 22.Which of these is good for training a model? (a) correct labels (b) copies of one photo (c) labels added at random (d) wrong labels
23. 23.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
24. 24.🔍 Which is the odd one out? (a) checking labels twice (b) many varied examples (c) only one kind of example (d) examples of every type
25. 25.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
26. 26.True or false: “clear, sharp examples” is good for training a model. (a) False (b) True
27. 27.Which of these is bad for training a model? (a) photos in many lights (b) many varied examples (c) examples of every type (d) testing on training data
28. 28.🔍 Which is the odd one out? (a) clear, sharp examples (b) blurry, unclear photos (c) checking labels twice (d) many varied examples
29. 29.Which of these is good for training a model? (a) clear, sharp examples (b) only one kind of example (c) very few examples (d) labels added at random
30. 30.🏷️ 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
31. 31.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
32. 32.🔍 Which is the odd one out? (a) wrong labels (b) only one kind of example (c) checking labels twice (d) testing on training data
33. 33.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
34. 34.🔍 Which is the odd one out? (a) wrong labels (b) copies of one photo (c) only one kind of example (d) many varied examples
35. 35.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
36. 36.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
37. 37.🏷️ 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
38. 38.True or false: “many varied examples” is good for training a model. (a) True (b) False
39. 39.🔍 Which is the odd one out? (a) blurry, unclear photos (b) testing on training data (c) new data for testing (d) wrong labels
40. 40.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) not spam (b) spam

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