title: Using neural network to predict next outcome
body: <p>I am struggling to understand how to use neural networks to predict some values.</p>
  
  <p>As I have understood, I can train my neural network with some time series.</p>
  
  <p>So if I have, for instance, the day-to-day quotes for a specific stock, I can train the network with these values.</p>
  
  <p>But if I have the day-to-day quotes as a vector <code>[42, 12, 20, 53, 18]</code> and I want to predict the next value, wouldn't it just be a linear regression problem with formula <code>Y = 0.7X + 31.1</code>, yielding <code>26.9</code> as the next (6th) value?</p>
  
  <p>Is neural networks only useful when the output relies on many inputs? Can someone show me a working example of how to predict the next outcome in a time series that shows that it's more useful to use neural networks rather than multivariate regression?</p>
  
  <p>I have, for instance, looked at <a href="https://github.com/cazala/synaptic" rel="nofollow">synaptic.js</a>, but they don't provide any simple examples to predict outcomes.</p>
  
  <p>I am very new at neural networks, so I am sorry if this question is really stupid :-D</p>