Cms3503 Machine Learning Assessment Answer

Question:

Please pay special attention to the assessment regulations (section 4) on Academic Misconduct

In brief: ensure that you;

1.DO NOT use the work of another student - this includes students from previous years and other institutions, as well as current students on the module.

2.DO NOT make your work available or leave insecure, for other students to view or use.

3.Any examples provided by the module tutor should be appropriately referenced, as should examples from external sources.

Further guidance can be found in the SCEN Academic Skills Resource and UoH Academic Integrity Resource module in Brightspace.

If you experience difficulties with this assessment or with time management, please speak to the module tutor/s, your Personal Academic Tutor, or the School’s Guidance Team.

Requesting an Extension You are reminded to ‘back-up’ your work as extensions will not be given for lost work, which includes work lost due to hardware and software failure/s.

Extension requests will only be approved if you can demonstrate genuine, unexpected circumstances along with independent supporting evidence (e.g medical certificate) that may prevent you submitting an assessment on time.

Submit an extension request via Student Portal within 2 working days of the due date.

Extension requests, up to a maximum of 10 working days, but typically 1-5 working days, will be considered provided that there is appropriate evidence which clearly indicates reasons for the request.

You will have 5 working days after submitting a request to provide the evidence. Failure to submit evidence will result in the request being rejected and your work being marked as a late submission.

If you are unable to submit work within the maximum extension period of 10 days, contact the School’s Guidance team ([email protected]), as you may need to submit a claim for Extenuating Circumstances (ECs).

Extenuating Circumstances (ECs) An EC claim is appropriate in exceptional circumstances, when an extension is not sufficient due to the nature of the request, or it concerns an examination or In-Class Test (ICT).

You will need to submit independent, verifiable evidence for your claim to be considered.

Once your EC claim has been reviewed you will get an EC outcome email from Registry.  If you are unsure what it means or what you need to do next, please speak to the Student Support Office – SJ1/01

An approved EC will extend the submission date to the next assessment period (e.g July resit period).

1.Investigation: You should produce a scholarly report concerning the use of the machine learning methods in the application area you’ve selected. You should evaluate both the appropriateness and the readiness of a set of ML techniques to a problem class. This weights 40% of the overall marks, and will be included in your final report. You should submit the literature survey by 27.03.20 for a formative feedback.

2.Development Task: You should then propose a software solution to the practical problem using machine learning method of your choice, which is to be documented in an evaluative report. This weights 60% of the overall marks, and will be included in your final report.

The final report should include:

A critical investigation of the associated literature

A description of the planned research, methodology and evaluation methods

A description of the experimental study undertaken

The findings of the work

·The report must be submitted electronically. The overall length of the report should be 6 pages including references and should be formatted according to the instructions above (please do not submit until your report is within this range). For word count that should be explicitly annotated in the report, it should be ~3000 words (excluding references). Note that it will be acceptable without penalty if the word count exceeds the permitted limit so long as it is within the page limit.

We require you to use a standard template for your report and have selected that of the IEEE conferences, which also supports the University’s prescribed referencing standard.  This will also make the transition from your report to a possible conference paper easier (in case of enough contributions to knowledge).