message: Example added
diff: @@ -116,6 +116,19 @@ def gradients(ys,
  sess.run(g2) # [array([[0., 0.]], dtype=float32)]
  ```
  + Let us take one practical example which comes during the back propogation phase.
  + This function is used to evaluate the derivatives of the cost function with
  + respect to Weights `Ws` and Biases `bs`. Below sample implementation provides
  + the exaplantion of what it is actually used for :
  +
  + ```python
  + Ws = tf.constant(0.)
  + bs = 2 * Ws
  + cost = Ws + bs # This is just an example. So, please ignore the formulas used.
  + g = tf.gradients(cost, [Ws, bs])
  + dCost_dW, dCost_db = g
  + ```
  +
  Args:
  ys: A `Tensor` or list of tensors to be differentiated.
  