The goal of this series is to provide content for beginners who wants to understand enough linear algebra to be confortable with machine learning and deep learning. However, I think that the chapter on linear algebra from the Deep Learning book is a bit tough for beginners. So I decided to produce code, examples and drawings on each part of this chapter in order to add steps that may not be obvious for beginners. I also think that you can convey as much information and knowledge through examples than through general definitions. The illustrations are a way to see the big picture of an idea. Finally, I think that coding is a great tool to experiment concretely these abstract mathematical notions. Along with pen and paper, it adds a layer of what you can try to push your understanding through new horizons.