Lecture: Using Python for industrial prototypes
At Semantic Web Company (semantic-web.com) we pursue the goal of applying complex scientific solutions to solve everyday tasks. This process has at least 3 major steps: (1) finding an appropriate model to solve the problem, (2) implementing a prototype of this model to test its feasibility, and (3) reimplementation of the prototype into our core product PoolParty (poolparty.biz).
In this talk I will primarily focus on step (2) and touch step (1). Because of its multi-purposeness and a large number of available packages Python is especially suitable for creating such prototypes. I will go through an app for natural language processing task to demonstrate the architecture I use in my working life. This example will illustrate how one can create a service on top of a PoolParty API.