title: Implement softmax function with numpy array
body: <p>My current function is as follows:</p>
  
  <pre><code>def soft_max(z):
      t = np.exp(z)
      a = np.exp(z) / np.sum(t, axis=1)
      return a
  </code></pre>
  
  <p>However I get the error: <code>ValueError: operands could not be broadcast together with shapes (20,10) (20,)</code> since np.sum(t, axis=1) isn't a scalar. </p>
  
  <p>I want to have <code>t / the sum of each row</code> but I don't know how to do this.  </p>