title: Are there alternatives to backpropagation?
body: <p>I know a neural network can be trained using gradient descent and I understand how it works.</p>
  
  <p>Recently, I stumbled upon other training algorithms: conjugate gradient and quasi-Newton algorithms.
  I tried to understand how they work but the only good intuition I could get is that they use higher order derivative.</p>
  
  <p>My questions are the following: are those alternative algorithms I mentioned fundamentally different from a backpropagation process where weights are adjusted by using the gradient of the loss function? 
  If not, is there an algorithm to train a neural network that is fundamentally different from the mechanism of backpropagation?</p>
  
  <p>Thanks</p>