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Class 7 AI Domains and Predictive Techniques: cheat sheet
CBSE Computational Thinking and AI. AI works in three main domains (Computer Vision, Natural Language Processing, Data Science) and predicts with classification, regression and clustering.
Key ideas
- Computer Vision works with images and video, such as reading number plates or naming a plant from a photo.
- Natural Language Processing (NLP) works with text and speech, such as translating or answering questions.
- Data Science finds patterns in numbers and records, such as rainfall trends or what a shop sells most.
- Classification puts things into labelled groups; regression predicts a number; clustering finds groups with no labels.
- A computer sees a black-and-white picture as a grid of pixels, each 1 (black) or 0 (white).
- A nearest-neighbour model labels a new item like the closest example it already knows.
Remember
| Regression with a steady change | value at step k = first value + (k − 1) × change |
| Example | 5, 8, 11, 14 cm in weeks 1–4 → week 8: 5 + 7 × 3 = 26 cm |
| Distance used here | difference in the first numbers + difference in the second |
| Two clusters | sort the numbers and split at the biggest gap |
| Pixels | percentage of 1s = black pixels ÷ all pixels × 100 |
| NLP first step | count how often each word appears |
Watch out
- Calling “predict tomorrow’s temperature” classification: a number to predict means regression.
- Using clustering when labels are given: with labels it is classification.
- Using k instead of k − 1 steps when continuing a pattern from step 1.
Worked example
A clustering method groups these times (in minutes) that children took to finish a puzzle into two clusters of close values: 63, 17, 19, 69, 22, 67, 66, 21. How many numbers are in the same cluster as 63 (counting 63)?
Working: in order: 17, 19, 21, 22, 63, 66, 67, 69; the biggest gap splits {17, 19, 21, 22} from {63, 66, 67, 69}
Answer: 4
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