Module Descriptor School of Computer Science and Statistics
|Module Name||Artificial Intelligence II / Machine Learning for Natural Langua|
|Module Short Title|
Lecture hours: 33, Lab hours: 11
|Module Personnel||Erwan Moreau, Liliana Mamani-Sanchez|
Know various ML methods, use a ML toolkit, complete a small Text categorisation system.
An in-depth introduction to AI and Machine Learning methods for NLP
Machine Learning for Natural Language Processing: Text categorisation, user-interface agents and issues, dimensionality reduction, probabilistic classification (Naive Bayes classifiers: multivariate Bernoulli, multinomial and continuous models), symbolic methods (decision trees, decision rules), instance-based methods (k-NN, case-based reasoning), other supervised methods (neural nets, SVM), unsupervised learning.
|Recommended Reading List|
Machine Learning for Natural Language Processing. European Summer School of Logic, Language and Information, by Martin Emms and Saturnino Luz (course reader. ESSLLI'07, Dublin, 2007)
Plus course notes.
Programming competence (e.g. CS 3011)
Exam (90%) and coursework (10%)
|Academic Year of Data|