From the course: LinkedIn AI Academy AI-100: 1 Demystifying AI

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Linear regression

Linear regression

- [Instructor] We saw in the last section that a regression comes in when there are two kinds of variables. One that we can observe, and the other that we cannot observe then and would want to predict. We try to find a relationship between these two types of variables and use the observable variables to predict the unknowns. The simplest relationship these two variables can take is a straight line, and this is called our linear regression. Linear regression is one of the simplest form of regression, and this technique is more than 200 years old. Let's continue with our working example of the creators on LinkedIn. As a creator, we want to understand what we might do to increase conversations on the content that we create. As a starting point, let's simplify it a bit and only look at text-based articles and understand the effect of the length of an article on the number of conversations that the article has. Again…

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