Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 369 · 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.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will be perfect (b) it will turn yellow (c) it will shut down (d) it may get it wrong
2. 2.True or false: “photos in many lights” is good for training a model. (a) True (b) False
3. 3.True or false: “many varied examples” is bad for training a model. (a) True (b) False
4. 4.🧠 Machine learning is a way for computers to… (a) print pages (b) charge faster (c) clean screens (d) learn from data
5. 5.🔍 Which is the odd one out? (a) copies of one photo (b) checking labels twice (c) wrong labels (d) only one kind of example
6. 6.📚 Good or bad for training a model: blurry, unclear photos? (a) bad for training (b) good for training
7. 7.📚 Good or bad for training a model: copies of one photo? (a) good for training (b) bad for training
8. 8.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) photos in many lights (d) testing on training data
9. 9.Which of these is bad for training a model? (a) examples of every type (b) new data for testing (c) labels added at random (d) checking labels twice
10. 10.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) a song about dogs (c) one single photo (d) many labelled photos
11. 11.True or false: “labels added at random” is bad for training a model. (a) True (b) False
12. 12.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
13. 13.Which of these is good for training a model? (a) correct labels (b) copies of one photo (c) blurry, unclear photos (d) labels added at random
14. 14.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the right answer tag (d) the price
15. 15.Which of these is bad for training a model? (a) checking labels twice (b) very few examples (c) examples of every type (d) clear, sharp examples
16. 16.Which of these is bad for training a model? (a) many varied examples (b) testing on training data (c) clear, sharp examples (d) checking labels twice
17. 17.True or false: the message “Match practice moved to 5 pm” should be labelled “spam”. (a) True (b) False
18. 18.📚 Usually, more good examples make a model… (a) slower to switch on (b) forget everything (c) change colour (d) better at its task
19. 19.🔍 Which is the odd one out? (a) many varied examples (b) copies of one photo (c) very few examples (d) wrong labels
20. 20.Which of these is good for training a model? (a) copies of one photo (b) labels added at random (c) many varied examples (d) wrong labels
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) spam (b) not spam
22. 22.🔍 Which is the odd one out? (a) labels added at random (b) blurry, unclear photos (c) testing on training data (d) examples of every type
23. 23.True or false: “clear, sharp examples” is bad for training a model. (a) True (b) False
24. 24.Which of these is good for training a model? (a) checking labels twice (b) testing on training data (c) only one kind of example (d) blurry, unclear photos
25. 25.Which of these is bad for training a model? (a) checking labels twice (b) many varied examples (c) new data for testing (d) wrong labels
26. 26.🏷️ 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
27. 27.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
28. 28.True or false: “photos in many lights” is bad for training a model. (a) False (b) True
29. 29.Which of these is bad for training a model? (a) photos in many lights (b) correct labels (c) only one kind of example (d) checking labels twice
30. 30.True or false: the message “Science project groups are on the board” should be labelled “not spam”. (a) True (b) False
31. 31.True or false: the message “You won a free phone! Click now!” should be labelled “not spam”. (a) False (b) True
32. 32.True or false: “only one kind of example” is good for training a model. (a) True (b) False
33. 33.Which of these is good for training a model? (a) labels added at random (b) only one kind of example (c) wrong labels (d) new data for testing
34. 34.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
35. 35.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
36. 36.📚 Good or bad for training a model: many varied examples? (a) good for training (b) bad for training
37. 37.🔍 Which is the odd one out? (a) only one kind of example (b) photos in many lights (c) labels added at random (d) copies of one photo
38. 38.🔍 Which is the odd one out? (a) correct labels (b) clear, sharp examples (c) photos in many lights (d) only one kind of example
39. 39.🔍 Which is the odd one out? (a) testing on training data (b) checking labels twice (c) photos in many lights (d) clear, sharp examples
40. 40.🏷️ 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

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