Text Mining 2020/21

Amsterdam University College -- Text Mining -- Winter/Spring 2021.

Contents

You can use the Hello World notebooks to check that everything is working.

Week	Topic	Materials
1	Introduction and Python refresher	slides + notebooks 1, 2, 3, 4, 5
2	Introduction to NLP and NLP pipelines	slides + notebook
3	Language modelling	slides + notebooks 1, 2
4	Vector space semantics	slides + notebook
5	Word embeddings	slides + notebook
6	Machine learning fundamentals and PyTorch	slides + notebook
7	Text classification
8	Advanced architectures and NER
9	Web scraping and APIs	notebook
10	Recommender systems	slides + notebook
11	Creating annotated corpora and sentiment analysis	slides + notebook
12	Clustering and topic modelling	slides + notebook
13	Trendy research topics

Group projects

See the projects folder for info.

Set-up

1. Clone the repository locally: git clone https://github.com/Giovanni1085/AUC_TMCI_2021.git
2. Get updates (from time to time): git pull
3. Create a conda environemnt: conda create -n myenv python=3.7 anaconda (where myenv is the envirnoment name)
4. Activate it: conda activate myenv
5. Install packages (see the requirements.txt file), e.g. conda install pandas
6. Launch a Jupyter notebook: jupyter notebook

• More on conda enviroments
• Conda cheatsheet
• Getting started with Jupyter notebooks
• On using git and GitHub for version control

Alternatively, use Binder (link above).

A more detailed guide to setup your environment, with multiple options.

Credits

• The previous-year edition of this course.
• Michael Repplinger, who ran the 2018/19 edition and Gianluca Lebani, who ran the 2017/18 edition.
• Giovanni Colavizza and Matteo Romanello, Applied Data Analysis course for the Oxford Digitial Humanities Summer School
• James Hetherington and Giovanni Colavizza, Research Software Engineering with Python

License

Everything in this repository which is not already attributed to someone else is released under CC BY 4.0.