1. What is the fundamental difference between an algorithm that uses linear regression and one that uses clustering? Please explain this difference clearly.

2. Explain the basic architecture of the perceptron - also known as the artificial 'neuron'. Please clearly explain typically what the inputs are, how it functions, and what is its output.

3. How exactly does a deep neural network learn? Please Explain clearly ad briefly just the top level concepts and processes involved. (Note: There are 3 main steps in the deep learning process.) Please make sure where the learning is captured.