Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 309 · 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 of these is good for training a model? (a) testing on training data (b) clear, sharp examples (c) wrong labels (d) blurry, unclear photos
2. 2.🔍 Which is the odd one out? (a) new data for testing (b) examples of every type (c) photos in many lights (d) only one kind of example
3. 3.True or false: the message “Science project groups are on the board” 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? “You won a free phone! Click now!” (a) spam (b) not spam
5. 5.🏷️ What is a “label” in machine learning? (a) the font size (b) the right answer tag (c) the price (d) a sticker on a laptop
6. 6.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
7. 7.🔍 Which is the odd one out? (a) photos in many lights (b) very few examples (c) many varied examples (d) checking labels twice
8. 8.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
9. 9.True or false: the message “Your library book is due on Monday” should be labelled “spam”. (a) False (b) True
10. 10.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
11. 11.🏷️ 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
12. 12.🔍 Which is the odd one out? (a) labels added at random (b) only one kind of example (c) wrong labels (d) correct labels
13. 13.Which of these is good for training a model? (a) testing on training data (b) only one kind of example (c) correct labels (d) labels added at random
14. 14.True or false: the message “Last chance! Free gift card inside” should be labelled “spam”. (a) False (b) True
15. 15.🔍 Which is the odd one out? (a) correct labels (b) wrong labels (c) photos in many lights (d) many varied examples
16. 16.🥭 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
17. 17.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) many labelled photos (c) a list of rules only (d) one single photo
18. 18.📚 Good or bad for training a model: only one kind of example? (a) good for training (b) bad for training
19. 19.📚 Good or bad for training a model: photos in many lights? (a) bad for training (b) good for training
20. 20.🧠 Machine learning is a way for computers to… (a) charge faster (b) learn from data (c) clean screens (d) print pages
21. 21.True or false: “only one kind of example” is bad for training a model. (a) False (b) True
22. 22.🏷️ 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
23. 23.Which of these is good for training a model? (a) examples of every type (b) wrong labels (c) copies of one photo (d) testing on training data
24. 24.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) better at its task (d) forget everything
25. 25.🔍 Which is the odd one out? (a) checking labels twice (b) new data for testing (c) labels added at random (d) many varied examples
26. 26.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) True (b) False
27. 27.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
28. 28.📚 Good or bad for training a model: new data for testing? (a) good for training (b) bad for training
29. 29.True or false: “labels added at random” is good for training a model. (a) True (b) False
30. 30.🏷️ 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
31. 31.🔍 Which is the odd one out? (a) labels added at random (b) very few examples (c) blurry, unclear photos (d) checking labels twice
32. 32.Which of these is bad for training a model? (a) new data for testing (b) checking labels twice (c) correct labels (d) copies of one photo
33. 33.True or false: “examples of every type” is bad for training a model. (a) True (b) False
34. 34.True or false: “correct labels” is good for training a model. (a) True (b) False
35. 35.📚 Good or bad for training a model: clear, sharp examples? (a) good for training (b) bad for training
36. 36.Which of these is good for training a model? (a) only one kind of example (b) checking labels twice (c) wrong labels (d) copies of one photo
37. 37.Which of these is bad for training a model? (a) new data for testing (b) photos in many lights (c) many varied examples (d) blurry, unclear photos
38. 38.True or false: “correct labels” is bad for training a model. (a) True (b) False
39. 39.🔍 Which is the odd one out? (a) testing on training data (b) new data for testing (c) wrong labels (d) blurry, unclear photos
40. 40.True or false: “very few examples” is bad for training a model. (a) True (b) False

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