MDA 5202 – MACHINE LEARNING KCA Masters Past Papers

UNIVERSITY EXAMINATIONS: 2019/2020
EXAMINATION FOR THE DEGREE OF MASTER OF SCIENCE IN
DATA ANALYICS
MDA 5202: MACHINE LEARNING
DATE: MAY 2020 TIME: 14 DAYS
INSTRUCTIONS: Answer ALL Questions

Take-Home Examination
QUESTION ONE
In his 1982 book Megatrends, John Naisbitt wrote “We are drowning in information but starved
for knowledge.” While written over 30 years ago, that line is as very true today. Every
organization has a great deal of data and more data is being collected every day such as COVID-19 data. However, data is useless unless you can convert it to information and ultimately into
knowledge. Machine learning techniques such as deep learning techniques are viewed as suitable
tools for creating models that can provide knowledge.
Requirements
– Write a research paper that proposes a deep learning model for predicting a certain
phenomenon in an organization, county or in Kenya.
– Submit a Zip file that consists downloaded data, Research paper and a document with
screen shots of python code and output
– The paper should be structured as follows:
1. Front Pages (3 Marks)
– Title page, Glossary, acronyms, Abstract and table of content
3. Introduction (10 Marks)
– Background of phenomenon and deep learning techniques
– Problem statement
– Objectives
-Significance of the study
4. Literature Review (10 Marks)
– Review of at least three studies that have used deep learning algorithms to perform
machine learning tasks for decision making support.
– Limitations on each of the reviewed studies.
5. Methodology (10 Marks)
– Description of the process used to develop deep learning model. Draw a well labelled
diagram to illustrate the process and cite the source of the process
– screen shots of python code used to implement various steps of the process and respective
outputs.

6. Results (10 Marks)
– Screen shots and interpretations of the visualized model.
– Description of evaluation results obtained after testing the proposed model

7. Conclusion and Recommendations (5 Marks)

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