Course: Advanced Learning Algorithms

Week 1 and 2

Hi all,

I am trying to understand what problem does Neural Networks solve.

In the coffee roasting example, I understand it would possible to draw the decision boundary using a polynomial equation using logistic regression, and hence predict all the ‘Good Roast’ beans. LogReg itself implements gradient descent.

I’d like to know why neural networks was introduced to address the same problem. It seems to implement the same thing with several neurons.

Another general question: what do we expect to accomplish by adding several neurons in various layers?

I am aware that I lack the necessary understanding, and I would be thankful for assistance.

Thanks