Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 392 · 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) many varied examples (b) copies of one photo (c) correct labels (d) photos in many lights
2. 2.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
3. 3.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
4. 4.📚 Usually, more good examples make a model… (a) change colour (b) forget everything (c) better at its task (d) slower to switch on
5. 5.Which of these is good for training a model? (a) many varied examples (b) wrong labels (c) testing on training data (d) blurry, unclear photos
6. 6.🏷️ What is a “label” in machine learning? (a) the font size (b) the price (c) a sticker on a laptop (d) the right answer tag
7. 7.🔍 Which is the odd one out? (a) clear, sharp examples (b) testing on training data (c) examples of every type (d) correct labels
8. 8.Which of these is bad for training a model? (a) new data for testing (b) many varied examples (c) checking labels twice (d) copies of one photo
9. 9.🔍 Which is the odd one out? (a) very few examples (b) photos in many lights (c) new data for testing (d) many varied examples
10. 10.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
11. 11.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
12. 12.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
13. 13.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will shut down (c) it may get it wrong (d) it will turn yellow
14. 14.🏷️ 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
15. 15.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
16. 16.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
17. 17.🔍 Which is the odd one out? (a) very few examples (b) testing on training data (c) wrong labels (d) correct labels
18. 18.Which of these is good for training a model? (a) new data for testing (b) testing on training data (c) only one kind of example (d) labels added at random
19. 19.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
20. 20.🧠 Machine learning is a way for computers to… (a) learn from data (b) clean screens (c) print pages (d) charge faster
21. 21.🏷️ 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
22. 22.True or false: “labels added at random” is good for training a model. (a) True (b) False
23. 23.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
24. 24.🏷️ 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) spam (b) not spam
25. 25.🐶 To teach a model to spot dogs in photos, what do you give it? (a) many labelled photos (b) a song about dogs (c) one single photo (d) a list of rules only
26. 26.🔍 Which is the odd one out? (a) labels added at random (b) wrong labels (c) checking labels twice (d) very few examples
27. 27.🏷️ 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
28. 28.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
29. 29.True or false: the message “Last chance! Free gift card inside” should be labelled “not spam”. (a) True (b) False
30. 30.Which of these is bad for training a model? (a) very few examples (b) photos in many lights (c) examples of every type (d) new data for testing
31. 31.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
32. 32.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
33. 33.🏷️ 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
34. 34.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
35. 35.Which of these is bad for training a model? (a) correct labels (b) labels added at random (c) many varied examples (d) new data for testing
36. 36.🏷️ 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
37. 37.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
38. 38.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) very few examples (d) checking labels twice
39. 39.🔍 Which is the odd one out? (a) only one kind of example (b) blurry, unclear photos (c) photos in many lights (d) testing on training data
40. 40.Which of these is bad for training a model? (a) photos in many lights (b) clear, sharp examples (c) wrong labels (d) examples of every type

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