Blog

ML Conference
The Conference for Machine Learning Innovation
9 - 11 December 2019 | Berlin

6
Aug

Neural networks with PyTorch

PyTorch is currently one of the most popular frameworks for the development and training of neural networks. It is characterized above all by its high flexibility and the ability to use standard Python debuggers. And you don’t have to compromise on the training performance. 
9
Jul

The Ethics of AI – dealing with difficult choices in a non-binary world

In the field of machine learning, many ethical questions are taking on new meaning: On what basis does artificial intelligence make decisions? How can we avoid the transfer of social prejudices to machine learning models? What responsibility do developers have for the results of their algorithms? In his keynote from the Machine Learning Conference 2019, Eric Reiss examines dark patterns in the ethics of machine learning and looks for a better answer than "My company won’t let me do that."
13
Jun

Reinforcement Learning: A gentle introduction and industrial application

Machine learning can be implemented in different ways, one of which is reinforcement learning. What exactly is reinforcement learning and how can we put it to use? Before the upcoming ML Conference, we spoke to Dr. Christian Hidber about the underlying ideas and challenges of reinforcement learning, and why it can be suited for application in an industrial setting.
6
May

Deep Learning with Java: Introduction to Deeplearning4j

Deep learning is now often considered to be the "holy grail" when it comes to developing intelligent systems. While fully automatic and autonomous machine learning is on the way, current solutions still require the understanding of a software developer or engineer. Deep learning, by contrast, is a sub-discipline of machine learning that promises deep-reaching learning success without human intervention and is oriented towards the function and operation of neural networks in the human brain.
24
Apr

Tutorial: Introduction to the R programming language

You already have some experience with SQL and are wondering how you could find solutions to problems in R? Then this article is just the thing you need! We’ll start with the basic elements of the language - with lots of specific sample code to help. Then we’ll take a look at how we can deal with data (this is where basic SQL skills are helpful, but not required). And last but not least, we'll look at use cases that can typically be solved with R.

Behind the Tracks