In this article, I compare two available R packages for using neural networks to model data: neuralnet and deepnet. Through the comparisons I highlight various challenges in finding good hyperparameter values. I show that some needed hyperparameters differ when using these two packages, even with the same underlying algorithmic approach. neuralnet was developed by Stefan Fritsch and Frauke Guenther with contributors Marc Suling and Sebastian M. Mueller. deepnet was created by Xiao Rong.