Natural Language Processing

Much of the world's knowledge is stored in the form of text, and accordingly, understanding and harnessing knowledge from text are key challenges. In this subject, students will learn computational methods for working with text, in the form of natural language understanding, and language generation. Students will develop an understanding of the main algorithms used in natural language processing, for use in a diverse range of applications including machine translation, text mining, sentiment analysis, and question answering. The programming language used is Python.

• 1Identify basic challenges associated with the computational modelling of natural language
• 2Understand and articulate the mathematical and/or algorithmic basis of common techniques used in natural language processing
• 3Implement relevant techniques and/or interface with existing libraries
• 4Carry out end-to-end research experiments, including evaluation with text corpora as well as presentation and interpretation of results
• 5Critically analyse and assess text-processing systems and communicate criticisms constructively