University | University of Technology Sydney (UTS) |
Subject | Machine Learning |
This is an essay writing work on the applications of machine learning and/or deep learning in the Finance field. Research relevant academic papers, reports or articles, and evaluate the application of ML and/or DL models. Alternatively, you may construct and demonstrate ML and/or DL models to achieve a function or application within the chosen area. Your essay should present your findings and analysis.
Robo-Advisor
Instruction
1. Your essay should be original.
2. Your essay should include (but not be limited to) the following key points. The listed Parts A, B, C and D are not the fixed structure of your essay. You may arrange the report content based on your findings.
3. While not required, you are encouraged if would like to construct a machine
learning or deep learning model(s) using Python to solve a problem of the
selected financial issue with real data. Students who could realise a reasonable
function would gain a higher score.
4. Make sure you read the Report Writing Guidelines carefully and pay attention to the length requirement.
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Question 1a
Introduction
This section should provide basic information about your study. It should cover the following points:
1. Introduce the selected financial topic.
2. Summarise a general history and evolution of the topic. You can use
visualisations such as charts or tables to present your findings effectively.
3. Discuss the key problems and (or) possible pain points.
Question 1b
Literature Review
In this section, you are to read at least three (3) academic papers or reports that are relevant to the discussed problem or pain points in Part A. And give a comprehensive summary to cover the following key points:
1. Describe and summarise the solutions to the listed problems and (or) pain
points using traditional methods and using machine learning and (or) deep
learning techniques.
2.Compare the two (2) approaches, and appraise the importance of machine
learning and (or) deep learning in the development of the topic and its ability
to solve these issues.
Question 1c
Case study
1. Select one to two (1-2) real applications (e.g. machine learning or deep
learning tools/services that a company has adopted), illustrate the design and
construction of the machine learning and (or) deep learning model(s) to tackle
the problem. You can either focus on just one particular application or choose
more than one and compare them.
2. Assess the performance of the model(s), which may compare with using
traditional models if available.
Question 1d
Discussion & Conclusion
This section should cover the following points
1. Summarise your study
2. Discuss your thoughts on the future trends of machine learning and (or) deep Learning applications in the selected finance field.
Length: should not exceed 12 pages (including the relevant graphs, tables,
screenshots, and appendices (if any), but excluding the cover page,
references, and programming code if applicable). Deduct 3 marks for
each extra page. Deduct a maximum of 10 marks for excessive page count. Font Style: Times New Roman
Font size: 11
Line spacing: 1.5
Margins: 1” for the top, bottom, right, and left
Include the page number on each page
The report must be self-contained. Further mark deductions will be imposed for poorly prepared reports. Pay attention to paraphrasing, and at all costs, avoid patchwriting. A significant penalty of up-to-25-mark deduction will be imposed if students are found to be sloppy in paraphrasing work from other sources. If plagiarism is suspected, the case will be handed over to the Exam Department for further investigation.
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