You can find the slides of the presentation Georg gave here (.pdf, 3MB). Original announcement: Thursday 08/03/2018 at 15:00 in room B1.09 The speaker for this meeting will be Georg Krempl, who will talk about an approach for learning from data with limited supervision. Here is a shortened abstract: Machine learning has become widely used throughout commerce, science,…

The meeting was a success! Click here (.pdf, 2MB) to download the updated slides with a worked-out example of how the PC algorithm works, and contact Oisín Ryan (mailto:o.ryan@uu.nl) if you’d like to know more about the Causality Reading Group. Thursday 22/02/2018 at 15:00 in room B1.09 For this meeting, MSDSlab is teaming up with its sister Causality…

We have four new books on computational social science for the MSDSlab library: If you want to read any, go to the library page!

Thursday 08/02/2018 at 15:00 in room B1.09 This meeting, Ayoub Bagheri (M&S, UMCU) gave an introduction to text mining in general and some of his work in particular. Here’s a quote: Text mining is the process of analyzing natural language text looking for useful and unknown patterns. In other words, text mining is the art of turning free…

Introducing: MSDSlab Sessions Data science is not only attending talks and discussing methods, but also analysing datasets and practical problem-solving. A true data scientist knows which methods to use as well as how to use them in an efficient way. This is why we are introducing MSDSlab Sessions. In the MSDSlab Sessions, a session leader…

For those who want to review the presentation, it is available here: GitHub at Utrecht (.pdf, 4.3 MB). The github repository Mislav showed at the end of the talk can be found on Mislav’s GitHub page or on our own GitHub page. Thursday 25/01/2018 at 13:30 at Sjoerd Groenmangebouw C0.24 GitHub, the world’s leading open source…

The last MSDSlab meeting of the year 2017 has been cancelled.

Thursday 30/11/2017 at 15:00 in room B1.09 This meeting is all about software, Daniel will go over construction of neural nets in Keras, an R interface to Google’s TensorFlow. Part of the meeting will be about how to perform class prediction using pieces of text. For example: can we infer from IMDB review texts whether they are positive or…

For the presentation, click here: Variational inference (PDF, 461KB) Thursday 16/11/2017 at 15:00 in room B1.09 How to estimate (incredibly) complex models? With machine and deep learning algorithms, we can model very complex systems. One of the downsides is that these models can become so complex that their estimation either becomes intractable or take a very long time. In this…

We had a full house this time! Thanks all for joining. As discussed near the end of the meeting, head over to keras.rstudio.com and try out the Reuters example (almost at the bottom). In the upcoming meeting about software, we will discuss this further. The presentation can be downloaded from here (.html download, 19MB)     Announcement:…