Lab: Human Language Technology

This lab deepens the practical understanding of the contents of the course "Statistical Natural Language Processing". Starting from existing natural language processing libraries includes the development, implementation, and evaluation of sophisticated computational approaches to a number of common tasks related to the analysis and synthesis of natural language. As such, this lab exemplifies the whole spectrum of typical statistical natural language processing techniques in a variety of common tasks.

• Recap of general python progamming concepts
• Task on representation in NLP
• Task on supervised classification
• Task on sequence labeling
• Task on neural networks and transformers

Required:

•     Knowledge of programming

•     Any course on natural language processing, machine learning, or artificial intelligence

 Recommended:

•     Master' course "Statistical Natural Language Processing" (ideally in parallel to the lab)

• Daniel Jurafsky and James H. Martin. 2009. Speech and Language Processing: An Introduction to Natural Language Processing, Speech Recognition, and Computational Linguistics. Prentice-Hall, 2nd edition. Free draft of third edition: Speech and Language Processing

• This lab should ideally be taken in parallel with the master's course "Statistical Natural Language Processing". The maximum number of participants is 30.