A deeper understanding of NNets (Part 1) -- CNNs – Towards Data Science

Deep Learning and AI were the buzz words for 2016; by the end of 2017, they have become more frequent and more confusing. So lets try and understand everything one at a time. We will look into the heart of Deep Learning i.e. Most variants of NNets are hard to understand and the underlying architectural components make them all sound (theoretically) and look (graphically) the same. Thanks to Fjodor van Veen from The Asimov Institute, we have a fair representation of the most popular variants of NNet architectures.