The goal of this post is to serve as a nice introduction to deep architectures before diving to read the original publications where they are described.
I feel there is a lack of help in the research community. A little bit of the time of one researcher by making nice visualizations, dashboards, demos or even videos could save the time of all the researchers coming after him/her, and innovation will grow faster.
My contribution is by giving intuition in understanding the evolution of the so used deep convolutional neural networks as the default option for computer vision problems.
1 LeNet(to be implemented)
2 VGG (to be implemented)
Source: Deep Learning on Medium