Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 584 · 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) labels added at random (b) testing on training data (c) blurry, unclear photos (d) checking labels twice
2. 2.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
3. 3.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) False (b) True
4. 4.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) checking labels twice (d) blurry, unclear photos
5. 5.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
6. 6.🏷️ 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
7. 7.Which of these is bad for training a model? (a) clear, sharp examples (b) correct labels (c) only one kind of example (d) many varied examples
8. 8.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) not spam (b) 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) spam (b) not spam
10. 10.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
11. 11.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) learn from data (d) clean screens
12. 12.Which of these is good for training a model? (a) copies of one photo (b) photos in many lights (c) testing on training data (d) very few examples
13. 13.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will shut down (c) it will turn yellow (d) it will be perfect
14. 14.True or false: “examples of every type” is bad for training a model. (a) False (b) True
15. 15.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a song about dogs (c) many labelled photos (d) a list of rules only
16. 16.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
17. 17.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
18. 18.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) False (b) True
19. 19.🔍 Which is the odd one out? (a) clear, sharp examples (b) checking labels twice (c) examples of every type (d) very few examples
20. 20.🔍 Which is the odd one out? (a) clear, sharp examples (b) testing on training data (c) many varied examples (d) correct labels
21. 21.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
22. 22.Which of these is bad for training a model? (a) examples of every type (b) new data for testing (c) blurry, unclear photos (d) photos in many lights
23. 23.🔍 Which is the odd one out? (a) very few examples (b) correct labels (c) labels added at random (d) copies of one photo
24. 24.Which of these is good for training a model? (a) checking labels twice (b) labels added at random (c) copies of one photo (d) only one kind of example
25. 25.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
26. 26.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
27. 27.🔍 Which is the odd one out? (a) clear, sharp examples (b) copies of one photo (c) correct labels (d) many varied examples
28. 28.🏷️ 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
29. 29.True or false: the message “You won a free phone! Click now!” should be labelled “spam”. (a) True (b) False
30. 30.🔍 Which is the odd one out? (a) many varied examples (b) clear, sharp examples (c) only one kind of example (d) correct labels
31. 31.🏷️ 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
32. 32.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “You won a free phone! Click now!” (a) spam (b) not spam
33. 33.True or false: the message “Please buy milk on the way home” should be labelled “spam”. (a) True (b) False
34. 34.Which of these is bad for training a model? (a) correct labels (b) photos in many lights (c) copies of one photo (d) clear, sharp examples
35. 35.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
36. 36.Which of these is bad for training a model? (a) correct labels (b) examples of every type (c) very few examples (d) many varied examples
37. 37.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) True (b) False
38. 38.True or false: “labels added at random” is good for training a model. (a) False (b) True
39. 39.🔍 Which is the odd one out? (a) correct labels (b) new data for testing (c) labels added at random (d) examples of every type
40. 40.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training

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