Machine Learning Project 3: Predict Salary using Polynomial Regression
Today I’ll be looking at the Polynomial Regression example.
#100DaysOfMLCode #100ProjectsInML
I’ll be using the example from the A-Z Machine Learning course on Udemy.
If you look at the image above which list the equations for all 3 types of Regression — you will notice that in Polynomial Regression we have the same variables x1 but it is raised to different powers.
For example
- instead of x2 — we have x1 raised to the power 2.
- instead of x3 — we have x1 raised to the power 3.
Let’s explore the dataset.
Dataset
First let’s look at the dataset. It is Position_Salaries.csv and can be found here.
It has 3 columns — “Position”, “Level” and “Salary” and describes the approximate salary range for an employee based on what level he falls under.
For example if an employee is a Manager — he falls in Level 4 and should get around $80,000.
Below is the dataset.
