Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 323 · 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) correct labels (b) many varied examples (c) checking labels twice (d) copies of one photo
2. 2.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
3. 3.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
4. 4.Which of these is bad for training a model? (a) correct labels (b) checking labels twice (c) testing on training data (d) new data for testing
5. 5.🏷️ 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
6. 6.🔍 Which is the odd one out? (a) correct labels (b) clear, sharp examples (c) new data for testing (d) labels added at random
7. 7.🥭 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 shut down (d) it will be perfect
8. 8.📚 Usually, more good examples make a model… (a) forget everything (b) change colour (c) slower to switch on (d) better at its task
9. 9.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) True (b) False
10. 10.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
11. 11.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) print pages (d) clean screens
12. 12.Which of these is good for training a model? (a) blurry, unclear photos (b) very few examples (c) testing on training data (d) many varied examples
13. 13.True or false: “copies of one photo” is good for training a model. (a) False (b) True
14. 14.True or false: “labels added at random” is good for training a model. (a) False (b) True
15. 15.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
16. 16.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) one single photo (c) a list of rules only (d) a song about dogs
17. 17.🔍 Which is the odd one out? (a) testing on training data (b) copies of one photo (c) wrong labels (d) examples of every type
18. 18.🔍 Which is the odd one out? (a) only one kind of example (b) testing on training data (c) copies of one photo (d) correct labels
19. 19.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
20. 20.🔍 Which is the odd one out? (a) very few examples (b) testing on training data (c) copies of one photo (d) clear, sharp examples
21. 21.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) new data for testing (d) wrong labels
22. 22.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
23. 23.🔍 Which is the odd one out? (a) wrong labels (b) blurry, unclear photos (c) labels added at random (d) checking labels twice
24. 24.🔍 Which is the odd one out? (a) testing on training data (b) clear, sharp examples (c) many varied examples (d) correct labels
25. 25.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) clear, sharp examples (d) labels added at random
26. 26.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
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 is the odd one out? (a) photos in many lights (b) only one kind of example (c) examples of every type (d) many varied examples
29. 29.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
30. 30.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the font size (d) the right answer tag
31. 31.🏷️ 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
32. 32.True or false: “only one kind of example” is good for training a model. (a) True (b) False
33. 33.🔍 Which is the odd one out? (a) many varied examples (b) wrong labels (c) very few examples (d) blurry, unclear photos
34. 34.🔍 Which is the odd one out? (a) photos in many lights (b) examples of every type (c) correct labels (d) blurry, unclear photos
35. 35.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
36. 36.Which of these is good for training a model? (a) examples of every type (b) very few examples (c) labels added at random (d) testing on training data
37. 37.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
38. 38.Which of these is bad for training a model? (a) examples of every type (b) very few examples (c) photos in many lights (d) correct labels
39. 39.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) blurry, unclear photos (d) examples of every type
40. 40.Which of these is bad for training a model? (a) photos in many lights (b) new data for testing (c) only one kind of example (d) correct labels

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