In this chapter
- what is linear regression
- fitting a line through a set of data points
- coding the linear regression algorithm in Python
- using Turi Create to build a linear regression model to predict housing prices in a real dataset
- what is polynomial regression
- fitting a more complex curve to nonlinear data
- discussing examples of linear regression in the real world, such as medical applications and recommender systems
In this chapter, we will learn about linear regression. Linear regression is a powerful and widely used method to estimate values, such as the price of a house, the value of a certain stock, the life expectancy of an individual, or the amount of time a user will watch a video or spend on a website. You may have seen linear regression before as a plethora of complicated formulas including derivatives, systems of equations, and determinants. However, we can also see linear regression in a more graphical and less formulaic way. In this chapter, to understand linear regression, all you need is the ability to visualize points and lines moving around.
Let’s say that we have some points that roughly look like they are forming a line, as shown in figure 3.1.
Figure 3.1 Some points that roughly look like they are forming a line
