Annotation for Machine Learning

Uitgebreide vaknaam	Annotation for Machine Learning
Leerdoelen	In this course, students will learn how to define an annotation goal for a given NLP task, how to collect a dataset, define an annotation model, evaluate and adjudicate the annotations, create a gold standard corpus, perform a variety of statistical analytics over the corpus, train several machine learning (ML) algorithms on the dataset by selecting effective features drawn from the annotations, evaluate the learned ML models and compare their evaluation results, come up with a (strong) baseline model for the initial NLP task.
Omschrijving	Annotated natural language data is a crucial component in natural language processing. Annotation of data is a process of adding meta information to the text in order to facilitate computers to learn natural language processing. The course will examine how annotation of natural language text can lead to increase the performance of machine learning algorithms. In particular, the course will teach a multistage process for building your own annotated natural language dataset (aka corpus) for training and testing machine learning algorithms for a particular task.
Uren per week	4
Onderwijsvorm	nog niet bekend
Toetsvorm	nog niet bekend
Vaksoort	bachelor
Coördinator	prof. dr. M. Nissim
Docent(en)	prof. dr. M. Nissim , student-assistent
Entreevoorwaarden
Opmerkingen
Opgenomen in	Opleiding Jaar Periode Type BSc Informatiekunde 1 semester II b verplicht