Mastering the architecture of a machine learning and deep learning solution means first, and above all, becoming an expert in designing the architecture of a solution and being able to explain it.
The early lines of a source code program are not just variable declaration lines; they represent the data flow graph that drives the computation of a neural network. These lines define the architecture of your solutions. They are critical to the future of an artificial intelligence solution.
The architecture of the solution, represented by TensorBoard, for example, serves two purposes. The first purpose defines the way the computation of the graph will behave. The second purpose is to use the architecture as a communication tool to sell your project to your team, management, prospects, and customers. Our environment defines our project and not simply our technical abilities...
