Linear regression is one of the most simple machine learning models. However, you should not dismiss this model by any means. As mentioned previously, it is an essential building block that is utilized in other models, and it has some very important advantages.
As discussed throughout this book, integrity in machine learning applications is crucial, and the simpler and more interpretable a model is, the easier it is to maintain integrity. In addition, because the model is simple and interpretable, it allows you to understand inferred relationships between variables and check your work mentally as you develop. In the words of Mike Lee Williams from Fast Forward Labs (in http://blog.fastforwardlabs.com/2017/08/02/interpretability.html):
The future is algorithmic. Interpretable models offer a safer, more productive, and ultimately more collaborative relationship...
