Applied Machine Learning Project
1. Identify problems that can be solved using machine learning.
2. Understand the characteristics of various machine learning methods and make informed decisions regarding what machine learning method(s) should be applied theoretically to a given problem.
3. Accurately understand the terminologies widely used in machine learning and data science and apply them in practice.
Word count (if relevant) 1500 (+/- 10%)
Assessment task details – provide a description of the Task:
In this assignment, you will identify a dataset for analysis and discuss Machine Learning techniques with specific reference to the machine learning problem relevant to the chosen dataset.
Task
For this assignment (assignment 1), you should first select an open-source research dataset. There are many sources of open-source datasets including:
Google Research
Kaggle
UC Irvine
After choosing the dataset, you should define and justify the Machine Learning problem that can be addressed using the chosen dataset. The justification should include a clear compare and contrast of different machine learning techniques, different algorithms, and why and how they apply to the chosen dataset. It is important that the discussion is tailored to the chosen dataset and the identified machine learning problem. Please follow the requirements set out in the below rubric.
Submission instructions – What should be the format of the submission? / Where should it be submitted?
A Word or PDF document only (only one document to be submitted), containing your assignment and a reference list. Any additional material should be put in an appendix at the end of the report. References should be presented using the IEEE referencing format. Please submit online via the appropriate Turnitin submission on the module space.
Hints and tips
All submitted work is expected to observe academic standards in terms of referencing, academic writing, use of language etc. Failure to adhere to these instructions may result in your work being awarded a lower grade than it would otherwise deserve.
All references must be presented using IEEE formatting.
