ELE00115M Neural Networks & Neural Computing
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Word Count : 1000 words
Assessment Overview
The assessment for Neural Networks & Neural Computing is to produce a six page written report. The report must be in the format of an IEEE Transactions journal article, and follow IEEE guidelines. Details for the content of the report are given below. The weighting for this report is 100% of the module mark.
Summary of Report Content
The report should be structured as a technical review article on Artificial Neural Networks. It should contain:
A short introduction to the field of Artificial Neural Networks and motivation for the learning rules you have chosen to describe. The background to and description of one method of supervised learning and one method of unsupervised learning. An example application of your chosen method of supervised learning, and an example application of your chosen method of unsupervised learning. General conclusions and a discussion of the relative merits of supervised vs unsupervised learning.
Detailed Description of Report Content and Structure
Your report should include all the following within the 6 page limit:
I. Abstract – A paragraph of no more than 150 words summarising the report.
II. Introduction – Introduction to Artificial Neural Networks and motivation for choosing the supervised and unsupervised learning rules you will describe.
III. Supervised and Unsupervised learning rules – A description of your chosen supervised and unsupervised learning rules. This should include the background to each learning rule and key equations. This section should be self-contained, it is not enough to simply refer to lecture notes or other published work.
IV. Example application of supervised and unsupervised learning – A description of and results from an example application for each method. This should include illustrations (appropriately referenced). You should also guide the reader through the interpretation of the results from each application.
V. Discussion – This section should summarise the main points from the review. It should contain a comparison of the relative merits and the strengths and weaknesses (or advantages and disadvantages) of the supervised and unsupervised learning rules you present.
VI. References – This section should be in IEEE format, make sure citations are complete, and that all sources are correctly acknowledged.
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The post ELE00115M Neural Networks & Neural Computing appeared first on Krita Infomatics.
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