Advanced Language Processing with Python

Arda Tezcan and Thierry Desot
Target group
Postgraduate CALM & EM-TTI

About Advanced Language Processing with Python

Advanced Language Processing with Python builds on previously acquired programming competencies in Python and focuses on the applications of the Natural Language Processing (NLP) techniques, which are thought in the course "Natural Language Processing". In this course, the students will learn to integrate NLP libraries (such as the Natural Language Toolkit (NLTK), NumPy and Scikit-Learn) into Python code and tackle NLP problems using supervised machine learning techniques, such as linear and logistic regression.

The course deals with the following topics:

  • Searching and manipulating text using regular expressions
  • Integrating NLP libraries into Python
  • Text pre-processing: tokenization, part-of-speech tagging, named entity recognition
  • Text normalization: stemming, lemmatization
  • Dependencies and dependency parsing
  • Feature engineering for NLP tasks
  • Introduction to supervised machine-learning
  • Visualizing data
  • Evaluating machine learning models