Machine Learning

School of Computing and Engineering

Title

Assessment Module

Machine Learning Module Code

CP70066E Module Leader:

Massoud Zolgharni Set by:

Massoud Zolgharni Moderated by:

Nasser Matoorian

Type of assessment: Coursework

Weighting: 100%

Assessor: Tutor

Each assignment has a specific weighting, and its own criteria.

• Assessment Item-1: Logbook on practical sessions – please contact the module leader if you have any questions

• (100%), due 3rd August 2020

You must achieve an overall mark of at least 50% to pass the module.

Feedback will be given within 15 working days.

1. Details of Assessment

This assessment is an individually assessed component. Please make sure you have

a clear understanding of the grading principles for this component. If you are unsure

about any aspect of this assessment component, please seek the advice of a member

of the delivery team.

The task involves data analysis, and discussion of methods and results, using Python.

For your report, you must submit a single PDF file that contains all answers, including

any text needed to describe your results, the example code snippets used to answer

each problem, any figures that were generated, and scans of any (clearly readable)

work on paper that you want the graders to consider. It is important that you include

enough detail that we know how you solved each problem.

You will need to ensure that your logbook is uploaded as a single PDF document. Note:

Documentary evidence (including source code listing) should be provided as

appropriate within your report. When submitting, name your PDF file using this format:

StudentID_LastName_ FirstName (for example: 12345678_Zolgharni_Massoud). You

must attend the lectures for further details, guidance and clarifications regarding these

instructions.

Assignments are to be submitted to Turnitin. You will find a link to the Turnitin

Assignments from the Assessments area of the Blackboard course menu. Turnitin

generates an Originality Report, and you are encouraged to make use of this facility as

a support tool to help you ensure the source material in your assignment is correctly

referenced before final submission.

At the due date and time, no further submissions or changes are possible. Whatever is

in the Turnitin inbox at this time will be regarded as your final submission.

Full details of the University Assessment Regulations can be found at:

http://www.uwl.ac.uk/students/current_students/Student_handbook.jsp

For guidance on online submission of assignments, including how to submit and how

to access online feedback, please refer to the UWL Blackboard student-help pages at:

http://www.uwl.ac.uk/blackboardhelp

Marking grid:

Criteria Issues Mark Marking

breakdown

where

appropriate

Learning

Outcomes

Report Critique the theory of machine learning

100

(total)

30

Apply a range of machine learning

techniques to solve practical problems

Critically evaluate and Interpret the

results

Quality of the report

30

30

10

LO1-LO4