Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 201 · 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? “Your account is locked, pay ₹99 now” (a) not spam (b) spam
2. 2.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
3. 3.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
4. 4.True or false: “photos in many lights” is good for training a model. (a) False (b) True
5. 5.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the price (c) the right answer tag (d) the font size
6. 6.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) many labelled photos (c) a list of rules only (d) a song about dogs
7. 7.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True
8. 8.🏷️ 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
9. 9.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
10. 10.Which of these is bad for training a model? (a) checking labels twice (b) examples of every type (c) new data for testing (d) labels added at random
11. 11.🔍 Which is the odd one out? (a) copies of one photo (b) blurry, unclear photos (c) new data for testing (d) only one kind of example
12. 12.📚 Good or bad for training a model: checking labels twice? (a) good for training (b) bad for training
13. 13.Which of these is good for training a model? (a) wrong labels (b) testing on training data (c) correct labels (d) copies of one photo
14. 14.Which of these is good for training a model? (a) examples of every type (b) testing on training data (c) only one kind of example (d) copies of one photo
15. 15.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
16. 16.🔍 Which is the odd one out? (a) correct labels (b) photos in many lights (c) many varied examples (d) blurry, unclear photos
17. 17.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
18. 18.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
19. 19.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
20. 20.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
21. 21.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will be perfect (c) it will shut down (d) it will turn yellow
22. 22.True or false: “only one kind of example” is good for training a model. (a) True (b) False
23. 23.📚 Good or bad for training a model: many varied examples? (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? “Please buy milk on the way home” (a) not spam (b) spam
25. 25.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) False (b) True
26. 26.Which of these is bad for training a model? (a) clear, sharp examples (b) new data for testing (c) correct labels (d) wrong labels
27. 27.Which of these is good for training a model? (a) blurry, unclear photos (b) very few examples (c) only one kind of example (d) clear, sharp examples
28. 28.📚 Good or bad for training a model: only one kind of example? (a) bad for training (b) good for training
29. 29.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
30. 30.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
31. 31.Which of these is good for training a model? (a) only one kind of example (b) blurry, unclear photos (c) photos in many lights (d) very few examples
32. 32.True or false: “wrong labels” is bad for training a model. (a) True (b) False
33. 33.🏷️ 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
34. 34.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) spam (b) not spam
35. 35.🔍 Which is the odd one out? (a) photos in many lights (b) correct labels (c) many varied examples (d) only one kind of example
36. 36.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
37. 37.Which of these is bad for training a model? (a) examples of every type (b) checking labels twice (c) correct labels (d) only one kind of example
38. 38.Which of these is bad for training a model? (a) new data for testing (b) very few examples (c) examples of every type (d) checking labels twice
39. 39.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) True (b) False
40. 40.🔍 Which is the odd one out? (a) wrong labels (b) labels added at random (c) very few examples (d) photos in many lights

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