CST4050 Coursework 2 (Individual Report)
Due date: 15/04/2022, 23:59
You can work in groups of up to 3 persons for data collection/processing only; you must present an individual report describing the approach and findings.
Description: This coursework is a free-form machine learning project, where the groups will be expected to identify a data-set to which machine learning techniques can be applied, and for which they will construct an appropriate methodological pipeline (in Python), evaluating the performance against relevant machine learning baselines. (This should be an original investigation and not an implementation of an existing pipeline e.g. Matlab face recognition).
Submission: You should submit a detailed report describing the steps above (1 submission per individual with any data collection group members cindicated). A Turnitin submission link will open on MyLearning in due course. The deadline for submission is 15/04/2022, 23:59. The report will carry 50% of the total mark for the course as a whole.
The report should consist of the following components:
- A clear description of the data-set & machine learning challenge
- A review of relevant machine learning literature
- A description of, and justification for, the machine learning pipeline adopted (explaining the choice of feature-selection/classification methodologies)
- An evaluation against appropriate baseline techniques
- A discussion/conclusion section summarising the findings
Your submission will be judged according to the following criteria: the appropriateness and challenge of the ML problem identified; the relevance of the techniques adopted; the structural clarity of report; the precision & clarity of language; the depth of technical understanding demonstrated; the thoroughness and validity of the evaluation; the awareness demonstrated of relevant aspects of machine learning theory.
