Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 282 · 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.True or false: “many varied examples” is bad for training a model. (a) True (b) False
2. 2.True or false: the message “Send your password to claim a prize” should be labelled “not spam”. (a) False (b) True
3. 3.True or false: “only one kind of example” is good for training a model. (a) False (b) True
4. 4.True or false: “correct labels” is bad for training a model. (a) True (b) False
5. 5.True or false: “testing on training data” is good for training a model. (a) True (b) False
6. 6.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) False (b) True
7. 7.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
8. 8.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
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) not spam (b) spam
10. 10.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) a list of rules only (c) many labelled photos (d) one single photo
11. 11.🏷️ 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
12. 12.True or false: “new data for testing” is good for training a model. (a) False (b) True
13. 13.🧠 Machine learning is a way for computers to… (a) clean screens (b) print pages (c) charge faster (d) learn from data
14. 14.True or false: “checking labels twice” is good for training a model. (a) False (b) True
15. 15.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
16. 16.Which of these is bad for training a model? (a) many varied examples (b) clear, sharp examples (c) labels added at random (d) new data for testing
17. 17.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) spam (b) not spam
18. 18.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) better at its task (d) forget everything
19. 19.🔍 Which is the odd one out? (a) only one kind of example (b) checking labels twice (c) new data for testing (d) examples of every type
20. 20.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
21. 21.🏷️ 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
22. 22.Which of these is bad for training a model? (a) blurry, unclear photos (b) correct labels (c) many varied examples (d) examples of every type
23. 23.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
24. 24.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
25. 25.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
26. 26.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
27. 27.True or false: “blurry, unclear photos” is bad for training a model. (a) False (b) True
28. 28.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) False (b) True
29. 29.🔍 Which is the odd one out? (a) only one kind of example (b) very few examples (c) checking labels twice (d) copies of one photo
30. 30.True or false: “copies of one photo” is good for training a model. (a) False (b) True
31. 31.🔍 Which is the odd one out? (a) photos in many lights (b) many varied examples (c) correct labels (d) wrong labels
32. 32.Which of these is bad for training a model? (a) photos in many lights (b) copies of one photo (c) many varied examples (d) correct labels
33. 33.True or false: “examples of every type” is good for training a model. (a) True (b) False
34. 34.🏷️ 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
35. 35.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) testing on training data (d) checking labels twice
36. 36.🏷️ 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
37. 37.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
38. 38.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) labels added at random (d) examples of every type
39. 39.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
40. 40.Which of these is good for training a model? (a) clear, sharp examples (b) very few examples (c) blurry, unclear photos (d) wrong labels

Free ai for students lessons, practice and worksheets at talentjr.in/ai-for-students