| layout | title | permalink |
|---|---|---|
page |
About |
/about/ |
Python has become a popular programming language in areas such as text and image analysis. The increase in popularity has been accompanied by the development of Jupyter notebooks. These browser-based environments allow users to combine blocks of code with text and images, increasing the accessibility of traceability of Python scripts.
In this tutorial, we will leverage notebooks to give learners an introduction to a number of text and image analysis approaches that are of interest to the humanities. The half-day, online event will begin with an introduction to the Jupyter notebook interface. Afterwards, a number of topics, such as document similarity, and clustering of handwritten characters, will be demonstrated and discussed using separate notebooks.
Overall, this tutorial aims to provide learners with the tools to work with existing notebooks, reading and understanding their contents and possibly adapting them to their own data and research questions. We expect no prior knowledge in Python and we will not try to cover the Python programming language in-depth. The tutorial is primarily aimed at students and researchers from the humanities but learners from all kinds of backgrounds and levels of prior knowledge are welcome.
- Diana Iusan, Uppsala Multidisciplinary Centre for Advanced Computational Science (UPPMAX), Sweden
- Kristoffer L. Nielbo, Center for Humanities Computing Aarhus, Denmark
- Nazeefa Fatima, ELIXIR Norway, University of Oslo, Norway
- Raphaela Heil, Centre for Image Analysis, Uppsala, Sweden
- Radovan Bast, UiT The Arctic University of Norway, Tromsø, Norway
- Henrik Askjer, University of Bergen Library, Norway
And many others, from institutions across the Nordic and Baltic Countries!