Traditional Business Intelligence (BI) deals with questions like “What has happend?” and “Why did it happen?”. In order to answer these questions BI software uses information derived from raw-data. On the other hand Advanced Analytics deals with questions like “What will happen?” and “How can we make it happen?”. These questions can be answered with Artificial Intelligence (AI) or more specific with machine learning techniques such as regression and neural networks. Usually such projects are more challenging to realise but provide much more business value compared to traditional BI.
We cover the whole range of analytics where our core competences are advanced analytics methods combined with our domain knowlege of physics, mechanical engeeering and forestry.
Introduction There are many blog posts comparing R and Python for data science but there are only a few about Wolfram vs. Python. In this post I will show some differences between Wolfram and Python and presume that you are familiar with Python but not with Wolfram. Python is now the most popular language for data science projects, while the Wolfram Language is rather a niche language in this concern.
As part of an interdisciplinary lecture series Andreas Trügler held two lectures this semester about digitalisation in science and society at the University of Graz. He discussed the basics of machine learning, artificial intelligence, and neural networks as well as important principles of digital data transmission, the internet of things, and big data. Besides a critical discussion of the social credit system in China and addressing the importance of privacy, data protection and digital security, he also presented various scientific examples of digitalisation, e.
Sorry, this blog post is available only in German.
Copyright (c) 2019, ATSEDA AB.
| VAT nr.: SE559161643701| Org. nr.: 559161-6437
