1.Rationalise appropriate scenarios for Machine Learning applications and evaluate the choice of machine learning methods for given application requirements.
2.Demonstrate competency in using appropriate libraries/toolkits to solve given real-world Machine Learning problems and develop and evaluate suitable application.
3.Understandand apply the relevant input data preparation and processing required for the Machine Learning models used, and quantitatively evaluate and qualitatively interpret the learning outcome.
4.Recognise and critically address the ethical, legal, social and professional issues that can arise when applying Machine Learning technologies.
Plagiarism is presenting somebody else’s work as your own. It includes: copying information directly from the Web or books without referencing the material; submitting joint coursework as an individual effort; copying another student’s course work; stealing course work from another student and submitting it as your own work. Suspected plagiarism will be investigated and if found to have occurred will be dealt with according to the procedures set down by the University. Please see your student handbook for further details of what is/ isn’t plagiarism.
All material copied or amended from any source (e.g. internet, books)must be referenced correctly according to the reference style you areusing.
Your work will be submitted for plagiarism checking. Any attempt to by pass our plagiarism detection systems will be treated as a severe Assessment Offence.
Coursework Submission Requirements
An electronic copy of your work for this course work must be fully uploaded on the Deadline Date using the link on the course work Moodle page for COMP1804.For this course work you must submit 4separate files:
- A single pdf file named‘ report.pdf’ which will be the written report; the written report must have a maximum limit of 3500 words including references. It is also recommended for the report to have at least 2000 words.
- A single csv file named‘ exclusions_dataset_taskX.csv’ (X is the number of the task you chose). The csv filewillincludealldata from yourdataset with an annotation as to whether each data pointhasbeen excluded from further analysis and why.Regardingthe format.