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DTSC301 Applied Machine Learning
Assignment
Weighting: 30%
Submit: your report and Jupyter Notebook (as .ipynb) via iLearn
Overview
Your task is to use what you have learned in the first 3 lectures and workshops to predict which
category newsgroup text belongs to.
I have uploaded a template notebook which contains the simplest possible solution, which you can use
as a starting point. Your goal is to build the best model you can. Remember a good model sits right at
the border between underfitting and overfitting – it maximizes accuracy while minimizing the
network size.
Report Template
Aim to produce a concise report. There is no need to introduce Deep Learning or the problem etc. in
any great detail.
A good approach is to use each of the 7 steps in the "Universal workflow of machine learning" as
guidance for sections / headings in your document. Naturally, you would also add a presentable title
page, exec summary, and conclusion.
Focus on explaining why you made the decisions and choices you made. I can see what you did in the
notebook code you upload… what I want to know is why you made those choices.
Marking thoughts
• I value conciseness and elegance in coding.
• I value your explanations as to why you made the choices you made.
• I value the quality of the model – higher test accuracy and a lower number of network
parameters makes a better model. Achieving this takes considerable effort and thought, which
will be rewarded.
o Ensure you show your test accuracy and call model.summary() on your final model
(once and once only!)