Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 335 · 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.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) not spam (b) spam
2. 2.Which of these is bad for training a model? (a) clear, sharp examples (b) examples of every type (c) checking labels twice (d) wrong labels
3. 3.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
4. 4.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will turn yellow (c) it will be perfect (d) it will shut down
5. 5.Which of these is bad for training a model? (a) only one kind of example (b) correct labels (c) photos in many lights (d) many varied examples
6. 6.🔍 Which is the odd one out? (a) photos in many lights (b) very few examples (c) only one kind of example (d) copies of one photo
7. 7.🔍 Which is the odd one out? (a) many varied examples (b) only one kind of example (c) labels added at random (d) very few examples
8. 8.True or false: “wrong labels” is bad for training a model. (a) False (b) True
9. 9.Which of these is bad for training a model? (a) photos in many lights (b) copies of one photo (c) new data for testing (d) checking labels twice
10. 10.📚 Usually, more good examples make a model… (a) forget everything (b) change colour (c) slower to switch on (d) better at its task
11. 11.True or false: “correct labels” is bad for training a model. (a) True (b) False
12. 12.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
13. 13.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) the price (d) a sticker on a laptop
14. 14.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
15. 15.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
16. 16.🏷️ 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
17. 17.True or false: “testing on training data” is bad for training a model. (a) True (b) False
18. 18.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
19. 19.Which of these is good for training a model? (a) labels added at random (b) copies of one photo (c) very few examples (d) correct labels
20. 20.True or false: “very few examples” is bad for training a model. (a) True (b) False
21. 21.True or false: the message “Science project groups are on the board” should be labelled “spam”. (a) False (b) True
22. 22.Which of these is bad for training a model? (a) correct labels (b) blurry, unclear photos (c) examples of every type (d) many varied examples
23. 23.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) False (b) True
24. 24.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
25. 25.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
26. 26.🔍 Which is the odd one out? (a) photos in many lights (b) many varied examples (c) correct labels (d) very few examples
27. 27.Which of these is bad for training a model? (a) many varied examples (b) testing on training data (c) checking labels twice (d) examples of every type
28. 28.True or false: “photos in many lights” is good for training a model. (a) False (b) True
29. 29.🔍 Which is the odd one out? (a) photos in many lights (b) checking labels twice (c) blurry, unclear photos (d) clear, sharp examples
30. 30.True or false: “copies of one photo” is good for training a model. (a) False (b) True
31. 31.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
32. 32.🔍 Which is the odd one out? (a) labels added at random (b) very few examples (c) wrong labels (d) examples of every type
33. 33.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
34. 34.🏷️ 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
35. 35.🏷️ 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
36. 36.True or false: “examples of every type” is good for training a model. (a) True (b) False
37. 37.🏷️ 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
38. 38.Which of these is good for training a model? (a) copies of one photo (b) blurry, unclear photos (c) wrong labels (d) new data for testing
39. 39.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
40. 40.Which of these is good for training a model? (a) testing on training data (b) blurry, unclear photos (c) examples of every type (d) copies of one photo

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