<p>Not a dedicated way :(</p>

<p>There's currently no easy (dedicated) way of doing this with Keras.</p>

<p>A discussion is ongoing at <a href="https://groups.google.com/forum/#!topic/keras-users/oEecCWayJrM" rel="noreferrer">https://groups.google.com/forum/#!topic/keras-users/oEecCWayJrM</a>.</p>

<p>You may also be interested in this paper: <a href="https://arxiv.org/pdf/1608.04493v1.pdf" rel="noreferrer">https://arxiv.org/pdf/1608.04493v1.pdf</a>.</p>
Pruning in Keras
<p>I'm trying to design a neural network using Keras with priority on prediction performance, and I cannot get sufficiently high accuracy by further reducing the number of layers and nodes per layer. I have noticed that very large portion of my weights are effectively zero (>95%). Is there a way to prune dense layers in hope of reducing prediction time?</p>