Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 598 · 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: “blurry, unclear photos” is bad for training a model. (a) False (b) True
2. 2.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) False (b) True
3. 3.True or false: “examples of every type” is bad for training a model. (a) True (b) False
4. 4.🔍 Which is the odd one out? (a) only one kind of example (b) copies of one photo (c) testing on training data (d) checking labels twice
5. 5.🔍 Which is the odd one out? (a) very few examples (b) labels added at random (c) wrong labels (d) clear, sharp examples
6. 6.Which of these is bad for training a model? (a) photos in many lights (b) testing on training data (c) examples of every type (d) clear, sharp examples
7. 7.Which of these is good for training a model? (a) labels added at random (b) clear, sharp examples (c) copies of one photo (d) very few examples
8. 8.🔍 Which is the odd one out? (a) checking labels twice (b) examples of every type (c) only one kind of example (d) photos in many lights
9. 9.🏷️ 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
10. 10.True or false: “only one kind of example” is bad for training a model. (a) True (b) False
11. 11.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
12. 12.True or false: “many varied examples” is bad for training a model. (a) False (b) True
13. 13.🧠 Machine learning is a way for computers to… (a) clean screens (b) learn from data (c) print pages (d) charge faster
14. 14.🔍 Which is the odd one out? (a) correct labels (b) many varied examples (c) labels added at random (d) examples of every type
15. 15.🏷️ 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
16. 16.🔍 Which is the odd one out? (a) testing on training data (b) photos in many lights (c) examples of every type (d) correct labels
17. 17.True or false: “blurry, unclear photos” is good for training a model. (a) False (b) True
18. 18.🏷️ 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
19. 19.📚 Good or bad for training a model: wrong labels? (a) good for training (b) bad for training
20. 20.📚 Good or bad for training a model: labels added at random? (a) good for training (b) bad for training
21. 21.True or false: “wrong labels” is good for training a model. (a) True (b) False
22. 22.True or false: “testing on training data” is good for training a model. (a) False (b) True
23. 23.True or false: “wrong labels” is bad for training a model. (a) True (b) False
24. 24.🔍 Which is the odd one out? (a) clear, sharp examples (b) blurry, unclear photos (c) many varied examples (d) photos in many lights
25. 25.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) one single photo (d) a list of rules only
26. 26.True or false: “testing on training data” is bad for training a model. (a) True (b) False
27. 27.Which of these is bad for training a model? (a) many varied examples (b) checking labels twice (c) copies of one photo (d) correct labels
28. 28.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
29. 29.Which of these is good for training a model? (a) testing on training data (b) blurry, unclear photos (c) checking labels twice (d) only one kind of example
30. 30.Which of these is bad for training a model? (a) many varied examples (b) very few examples (c) correct labels (d) photos in many lights
31. 31.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
32. 32.Which of these is good for training a model? (a) blurry, unclear photos (b) new data for testing (c) wrong labels (d) copies of one photo
33. 33.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will be perfect (c) it will shut down (d) it may get it wrong
34. 34.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
35. 35.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
36. 36.🏷️ 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
37. 37.Which of these is good for training a model? (a) very few examples (b) only one kind of example (c) wrong labels (d) many varied examples
38. 38.True or false: “labels added at random” is good for training a model. (a) False (b) True
39. 39.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Share your OTP to get cashback” (a) spam (b) not spam
40. 40.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training

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