The article recommends getting a 580 as the cheapest, most cost-effective option. One thing the 580 has going against it is that the cuDNN library does not support it. Only Kepler and Maxwell cards (600, 700 and 900 series) are supported. Since many of the popular libraries for deep learning (Theano, Caffe, Torch7) support using cuDNN as a backend now, I think this is worth mentioning. For many configurations cuDNN provides some of the fastest convolution implementations available right now. Even if the 580 is a great card for CUDA, a more recent model may actually be a better choice in light of this.

I agree 100% with the 980 recommendation, it's a great card in terms of performance, power usage and price point.