Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 434 · 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? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
2. 2.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
3. 3.🏷️ 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
4. 4.🧠 Machine learning is a way for computers to… (a) learn from data (b) charge faster (c) clean screens (d) print pages
5. 5.🔍 Which is the odd one out? (a) very few examples (b) testing on training data (c) blurry, unclear photos (d) checking labels twice
6. 6.📚 Good or bad for training a model: testing on training data? (a) bad for training (b) good for training
7. 7.🐶 To teach a model to spot dogs in photos, what do you give it? (a) one single photo (b) a list of rules only (c) many labelled photos (d) a song about dogs
8. 8.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
9. 9.True or false: “labels added at random” is bad for training a model. (a) True (b) False
10. 10.🔍 Which is the odd one out? (a) testing on training data (b) copies of one photo (c) new data for testing (d) blurry, unclear photos
11. 11.True or false: “checking labels twice” is bad for training a model. (a) False (b) True
12. 12.🏷️ 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
13. 13.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Science project groups are on the board” (a) not spam (b) spam
14. 14.🏷️ 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
15. 15.Which of these is bad for training a model? (a) many varied examples (b) correct labels (c) wrong labels (d) clear, sharp examples
16. 16.📚 Good or bad for training a model: very few examples? (a) good for training (b) bad for training
17. 17.True or false: the message “Please buy milk on the way home” should be labelled “not spam”. (a) False (b) True
18. 18.True or false: “photos in many lights” is good for training a model. (a) True (b) False
19. 19.True or false: “only one kind of example” is good for training a model. (a) True (b) False
20. 20.Which of these is bad for training a model? (a) examples of every type (b) checking labels twice (c) new data for testing (d) very few examples
21. 21.🔍 Which is the odd one out? (a) photos in many lights (b) very few examples (c) checking labels twice (d) correct labels
22. 22.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
23. 23.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
24. 24.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
25. 25.🔍 Which is the odd one out? (a) examples of every type (b) wrong labels (c) labels added at random (d) copies of one photo
26. 26.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
27. 27.🔍 Which is the odd one out? (a) clear, sharp examples (b) many varied examples (c) photos in many lights (d) blurry, unclear photos
28. 28.True or false: “very few examples” is good for training a model. (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) correct labels (d) only one kind of example
30. 30.True or false: “many varied examples” is good for training a model. (a) False (b) True
31. 31.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
32. 32.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it may get it wrong (b) it will turn yellow (c) it will shut down (d) it will be perfect
33. 33.🏷️ What is a “label” in machine learning? (a) the price (b) the right answer tag (c) the font size (d) a sticker on a laptop
34. 34.Which of these is good for training a model? (a) very few examples (b) copies of one photo (c) clear, sharp examples (d) labels added at random
35. 35.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “not spam”. (a) False (b) True
36. 36.📚 Usually, more good examples make a model… (a) slower to switch on (b) better at its task (c) change colour (d) forget everything
37. 37.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “spam”. (a) False (b) True
38. 38.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
39. 39.True or false: “correct labels” is bad for training a model. (a) False (b) True
40. 40.True or false: “examples of every type” is bad for training a model. (a) False (b) True

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