Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Machine Learning Mode

The video tutorial discusses the distinction between linear and nonlinear models, focusing on linearity in parameters W1 and W2. It explores whether adding a constant affects the linearity of a model and provides a method to check linearity using matrix multiplication. The tutorial emphasizes understanding linearity in parameters rather than inputs.

Discuss the implications of a model being linear in parameters.

What method was suggested to check for linearity in the previous discussion?