Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 179 · 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.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
2. 2.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
3. 3.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) True (b) False
4. 4.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your account is locked, pay ₹99 now” (a) spam (b) not spam
5. 5.🏷️ 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
6. 6.🔍 Which is the odd one out? (a) examples of every type (b) wrong labels (c) clear, sharp examples (d) photos in many lights
7. 7.🏷️ 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
8. 8.Which of these is bad for training a model? (a) copies of one photo (b) new data for testing (c) checking labels twice (d) examples of every type
9. 9.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
10. 10.True or false: “only one kind of example” is good for training a model. (a) True (b) False
11. 11.Which of these is bad for training a model? (a) new data for testing (b) correct labels (c) photos in many lights (d) wrong labels
12. 12.Which of these is good for training a model? (a) labels added at random (b) wrong labels (c) many varied examples (d) copies of one photo
13. 13.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) True (b) False
14. 14.🏷️ 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
15. 15.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
16. 16.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
17. 17.🔍 Which is the odd one out? (a) only one kind of example (b) very few examples (c) testing on training data (d) correct labels
18. 18.🥭 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
19. 19.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
20. 20.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) charge faster (d) print pages
21. 21.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
22. 22.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
23. 23.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
24. 24.Which of these is good for training a model? (a) very few examples (b) photos in many lights (c) testing on training data (d) blurry, unclear photos
25. 25.True or false: “very few examples” is good for training a model. (a) True (b) False
26. 26.Which of these is good for training a model? (a) very few examples (b) new data for testing (c) labels added at random (d) wrong labels
27. 27.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
28. 28.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
29. 29.🔍 Which is the odd one out? (a) examples of every type (b) only one kind of example (c) checking labels twice (d) many varied examples
30. 30.🔍 Which is the odd one out? (a) photos in many lights (b) clear, sharp examples (c) examples of every type (d) very few examples
31. 31.Which of these is good for training a model? (a) labels added at random (b) testing on training data (c) checking labels twice (d) blurry, unclear photos
32. 32.True or false: “blurry, unclear photos” is good 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? “The class picnic is on Friday at 8 am” (a) spam (b) not spam
34. 34.Which of these is bad for training a model? (a) examples of every type (b) new data for testing (c) testing on training data (d) checking labels twice
35. 35.🔍 Which is the odd one out? (a) wrong labels (b) labels added at random (c) many varied examples (d) copies of one photo
36. 36.True or false: the message “Share your OTP to get cashback” should be labelled “spam”. (a) False (b) True
37. 37.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) True (b) False
38. 38.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) False (b) True
39. 39.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) a song about dogs (d) many labelled photos
40. 40.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) not spam (b) spam

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