CS365 : Neural Networks

Contacts

Aim

Neural computing techniques seem to offer a way in which a simple mathematical model can be applied to solve complex problems through the suitable selection and training on examples. This artificial intelligence technique has been used for a wide range of applications from the simulation of psychological abilities to predicting stock market prices. The module will examine the biological background of neural computing techniques, provide a foundation on the common approaches to modelling neurons, and then explore example algorithms for supervised and unsupervised learning.

The notes and resources for this module are available on ULearn. Access to the notes will be given to subscribed students for the Spring semester. If you are not currently subscribed for this module and would like access, please get in touch. Notes for the first, introductory lecture are available here (PDF 185Kb).

Disclaimer

Every effort has been made to ensure the accuracy of the information contained in the University's web pages and in the associated School/Department pages. The University reserves the right to make changes to the information given. Applicants will receive additional, current information during the admissions process and on joining the University.