AI engineering glossary · Classical ML algorithms
What is simple linear regression?
Simple linear regression: The one-feature case of fitting a straight line to data: y = b0 + b1 * x. The slope b1 says how much the prediction changes for a one-unit rise in x, and the intercept b0 is the prediction when x is zero. It is the easiest model to plot and explain.
Simple linear regression: an example
Fitting exam score against hours studied gives score = 35 + 6 * hours, so each extra study hour adds about 6 marks and a student who studies 5 hours is predicted 65.
Related terms
More Classical ML algorithms terms
- Soft margin
- Softmax regression
- Spectral clustering
- Stacking
- Support
- Support vector
- Support vector machine
- Support vector regression
Where you learn it
Simple linear regression is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.