Natural Language Processing II – NLP Tasks

The methods of supervised and unsupervised learning can be applied to data that arises in non-numeric or non-categorical formats, such as text or images. The challenge there is often to find a way to transform the unstructured data into structured objects that can be fed into classification or clustering algorithms, say. In this course, we discuss other applications of natural language processing: named-entity recognition, semantic parsing, summarization, etc.