Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 289 · 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) many varied examples (b) new data for testing (c) wrong labels (d) correct labels
2. 2.Which of these is good for training a model? (a) copies of one photo (b) only one kind of example (c) checking labels twice (d) very few examples
3. 3.True or false: “clear, sharp examples” is bad for training a model. (a) False (b) True
4. 4.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a list of rules only (b) one single photo (c) many labelled photos (d) a song about dogs
5. 5.True or false: the message “Your library book is due on Monday” should be labelled “not spam”. (a) True (b) False
6. 6.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
7. 7.📚 Good or bad for training a model: examples of every type? (a) good for training (b) bad for training
8. 8.📚 Usually, more good examples make a model… (a) change colour (b) slower to switch on (c) better at its task (d) forget everything
9. 9.True or false: “testing on training data” is good for training a model. (a) True (b) False
10. 10.📚 Good or bad for training a model: wrong labels? (a) bad for training (b) good for training
11. 11.Which of these is good for training a model? (a) copies of one photo (b) wrong labels (c) new data for testing (d) testing on training data
12. 12.🧠 Machine learning is a way for computers to… (a) clean screens (b) charge faster (c) print pages (d) learn from data
13. 13.True or false: the message “Your account is locked, pay ₹99 now” should be labelled “not spam”. (a) True (b) False
14. 14.True or false: “blurry, unclear photos” is good for training a model. (a) True (b) False
15. 15.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
16. 16.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the right answer tag (c) the font size (d) the price
17. 17.🔍 Which is the odd one out? (a) only one kind of example (b) blurry, unclear photos (c) very few examples (d) photos in many lights
18. 18.📚 Good or bad for training a model: checking labels twice? (a) bad for training (b) good for training
19. 19.🥭 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 be perfect (d) it will turn yellow
20. 20.🔍 Which is the odd one out? (a) labels added at random (b) many varied examples (c) wrong labels (d) only one kind of example
21. 21.📚 Good or bad for training a model: testing on training data? (a) good for training (b) bad for training
22. 22.🔍 Which is the odd one out? (a) labels added at random (b) clear, sharp examples (c) photos in many lights (d) new data for testing
23. 23.True or false: “correct labels” is bad for training a model. (a) True (b) False
24. 24.🏷️ 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
25. 25.🔍 Which is the odd one out? (a) photos in many lights (b) clear, sharp examples (c) copies of one photo (d) many varied examples
26. 26.🔍 Which is the odd one out? (a) new data for testing (b) many varied examples (c) blurry, unclear photos (d) photos in many lights
27. 27.Which of these is good for training a model? (a) clear, sharp examples (b) wrong labels (c) labels added at random (d) copies of one photo
28. 28.Which of these is good for training a model? (a) only one kind of example (b) blurry, unclear photos (c) examples of every type (d) very few examples
29. 29.True or false: “testing on training data” is bad 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? “Share your OTP to get cashback” (a) not spam (b) spam
31. 31.Which of these is good for training a model? (a) labels added at random (b) many varied examples (c) wrong labels (d) copies of one photo
32. 32.🔍 Which is the odd one out? (a) testing on training data (b) correct labels (c) only one kind of example (d) very few examples
33. 33.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “spam”. (a) False (b) True
34. 34.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) not spam (b) spam
35. 35.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) True (b) False
36. 36.🔍 Which is the odd one out? (a) photos in many lights (b) checking labels twice (c) only one kind of example (d) many varied examples
37. 37.📚 Good or bad for training a model: copies of one photo? (a) bad for training (b) good for training
38. 38.🏷️ 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
39. 39.🔍 Which is the odd one out? (a) photos in many lights (b) correct labels (c) new data for testing (d) testing on training data
40. 40.Which of these is good for training a model? (a) wrong labels (b) only one kind of example (c) copies of one photo (d) correct labels

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