Machine Learning Project 4: Predict Salary using Support Vector Regression
Today I’ll be looking at the Support Vector Regression (SVR) example from the A-Z Machine Learning course on Udemy.
#100DaysOfMLCode #100ProjectsInML
We will be working on the same problem that we worked on Project 3. Here instead of using Polynomial Regression, we will use Support Vector Regression and see whether the prediction is better or worse compared to Polynomial Regression.
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.
