This talk is aimed at developers who need to pre-process data for their "AI model training" without a lot of science work and lengthy data preparation. After the short time that has passed since the hype around AI, there are quite a few approaches and pre-trained models that can be used.
My talk will demonstrate a practical approach from the field of vision. The goal is to use the example of the development of an own object detection, which recognizes not only car, person etc., but special objects like garbage can or mother-in-law. The necessary data collection and processing of this is in the foreground. I will discuss simple ways to quickly process the gigabytes of image material in order to achieve quick results. With a few simple steps, the participants can generate their own AI models in their own projects and quickly become creative in building them out in their own ways.
At the end of the talk, a demo will show the way from raw data to a simple application that uses our trained model and recognizes different objects.

This talk is aimed at software developers who already have some experience with AI and not much with the subject area DataScientists.
My intention is to bring the topic of AI closer to developers, as I believe that in the near future AI will be increasingly dominated by software developers.
For my talk I need some space on a table, as I am setting up a small "IoT" hardware that is supposed to recognize things with a WebCam.