AI on the Edge - Building a Machine Learning Cluster with Nvidia Jetson
The topic of AI is discussed in the media in terms of artificial consciousness, while the actual machine-learning applications have long been an integral part of the success of IT giants. To understand this technology it is essential to understand the principles of modern network architecture and its data structure and transmission. The course will take a practical approach to this topic and then lead into an informed discussion that will go beyond the opinions of "gift book philosophers".
The course gives an introduction to machine learning and its programming in Python using Nvidia Jetson Nano Computers set up as a Cloud-Cluster, that we set up in the seminar.
Every student will be provided with a NvidiaJetson Nano Developer Kit, from university (as a rental). https://developer.nvidia.com/embedded/jetson-nano-developer-kit
You get a basic understanding of:
- Linux operating system - Network structures - Video processing (OpenCV and ffmpeg)
- machine learning (basic models) - classification with neural networks
optional (advanced):
- docker containers
Though the general outline of the seminar is fixed, certain topics can be adopted to the demands of the projects and wishes of the students.
Programming knowledge in Python is mandatory.
The aim of the course is to gain a critical understanding of machine learning and its application. The course focuses on the analysis of classification of video streams and their classification.
Another central topic is cloud infrastructures and the so-called "edge computing" or "Internet of Things", which together with machine learning, form an almost all-encompassing set of tools for data collection that is beyond any (state) control. The course is therefore also suitable for those who are interested in a critical examination of "AI".