This was our final reading from *Neural Networks and Deep Learning*. This
chapter explained the basics of convolutional networks. It goes on to talk
about the ImageNet competition and the amazing progress in image recognition.
The chapter talks about the basics of RNNs and LSTMS and ends with some
predictions for future directions in deep learning research. The post is
originally from 2015, but it reads like it could have been written in 2019.