<p>It totally depends on the problem you try do model. The more layers you have, the harder it's to train the network (more computation power needed). The deeper the layer is however, the more complex problems it can solve.</p>

<p>Geoffrey Hinton wrote in his <a href="http://www.cs.toronto.edu/~hinton/nipstutorial/nipstut3.pdf" rel="noreferrer">tutorial</a>:</p>

<blockquote>
  <p>How many lines of code should an AI program use and how long should
  each line be? – This is obviously a silly question.</p>
  
  <p>• Deep belief nets
  give the creator a lot of freedom. </p>
  
  <p>– How best to make use of that
  freedom depends on the task. </p>
  
  <p>– With enough narrow layers we can model
  any distribution over binary vectors (Sutskever &amp; Hinton, 2007) </p>
  
  <p>• If freedom scares you, stick to convex optimization of shallow models
  that are obviously inadequate for doing Artificial Intelligence.</p>
</blockquote>

<p>From what I know the number of layers usually is not really big. <a href="http://arxiv.org/pdf/1409.4842.pdf" rel="noreferrer">Here</a> ( <em>ImageNet Large-Scale Visual Recognition Challenge 2014</em>) e.g. google team used a net with 22 layers.</p>
How many hidden layers are there in a Deep Neural Network
<p>can anybody tell me "usually" how many layers does a Deep Neural Network have? How deep is deep enough?</p>

<p>To my knowledge, it is still difficult to say the specific number of the hidden layers. But can anyone tell me, like some examples, how many hidden layers will researchers, developers use in their deep learning projects?</p>

<p>Many thanks.</p>