As part of the Winter School 20/21 Learn about Linguistic Data Science we offer two workshops for interested students independently of the classes during the winter semester. Participating in those courses will give you the necessary background knowledge to participate successfully in these workshops though. Students who have not taken the online courses will be required to hand in a small programming task to qualify for participation.
Information on Registration can be found here.
Workshop: NN in Python
This workshop will deal with neural network applications in Linguistic Data Science.
In this workshop we will understand how to apply a neural network to an NLP task using Python. We will focus on a concrete example but also discuss general technology and the thought processes necessary to solve a problem with NN.
We will see that recent technology achieves robust results and discuss the generalization problem across data sets
Workshop: From Data to Explanation
Annotated corpus data and data from linguistic experimentation form the two major resources to develop data-based explanations in linguistics.
This workshop addresses how corpus and experimental data can be structured and analyzed with generalized linear mixed models in R (using libraries such as lme4, tidyverse, emmeans, and ordinal).
Our data will be based on (open) grammatical problems such as the conditions for omitting a determiner (Kiss 2019), or word order variations.