title: How does a gradient descent algorithm work when it is already in a local minimum
body: <p>In the context of gradient <code>descent algorithms</code>, (not linear regression), if the cost function is already at a local minimum, what happens next? or how does it reach the global optimum later on?</p>
  
  <blockquote>
    <p>In the case of linear regression there is only one minimum, and hence
    no problem of a local minimum. But what about other algorithms that
    might have a local minimum and a global minimum?</p>
  </blockquote>