Dears, I am new in applying machine learning models. I am confused about the steps that should be applied to know exactly the type of regression model that should be used for my dataset. I read a lot and am confused now.

Should I follow the following?

1- Visualize the data

2- If it has a linear pattern, apply linear regression. If not, should I apply the non-linear model?

OR

Should I apply the linear model directly because it is easier to interpret? and it is okay to apply the linear model on non-linear datasets as shown here in this link:

Note: I want to find the correlation between 1 continuous dependent variable and multiple continuous independent variables

I hope to help me with that

You will need to provide more detail about your dataset.