1. Demonstrate knowledge of the fundamental principles of natural language processing. 2. Demonstrate understanding of key algorithms for natural language processing. 3. Write programs that process language. 4. Design your own end-to-end projects in NLP. 5. Evaluate the performance of programs that process language. 6. Assess feasibility and appropriateness of novel NLP approaches presented in literature.

Temps présentiel : 30 heures

Charge de travail étudiant : 100 heures

Méthode(s) d'évaluation : Evaluation - Examen final, Evaluation - Examen partiel

Référence :
Ekaterina Kochmar (2022). Getting Started with Natural Language Processing. Manning Publications, ISBN: 9781617296765. URL: Manning; Amazon; for the students at the University of Bath, the book is available via the university’s library service. Dan Jurafsky and James H. Martin (2009). Speech and Language Processing (2nd edition). Prentice-Hall Inc., Upper Saddle River, NJ, USA. ISBN: 0131873210. URL: 2nd edition; 3rd edition Steven Bird, Ewan Klein, and Edward Loper (2009). Natural Language Processing with Python. O’Reilly Media, Inc. ISBN: 978-0-596-51649-9. URL: NLTK book