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:

https://nadeemm.medium.com/linear-regression-using-non-linear-data-understanding-ordinary-least-squares-ols-561f37d2c95e#:~:text=Linear%20regression%20is%20a%20powerful,relationships%20between%20variables%20as%20well.

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

I hope to help me with that