Learn how to write programs that analyze written language.
The course will balance theoretical foundations with practical examples using the Python programming language.
No prior experience with libraries such as NLTK or scikit-learn is required for this course.
1 - Foundations
This first section provides the basic tools and techniques to get started with Natural Language Processing
Overview on NLP applications and the Python
Working with text
Word frequencies and co-occurrences
2 - Topic Modelling
This section aims at improving our understanding of a document, or a collection of documents, using techniques that go beyond simple word frequencies.
3 - Text Classification
This section tackles the problem of classifying documents into a set of predefined categories.
4 - Overview on Advanced Applications
The last section offers an outlook on advanced NLP problems, so delegates are equipped with ideas and techniques to tackle more specific applications
Named Entity Recognition
Natural Language Generation