UCI Programming Usefulness of Clustering Bayes Rule & Neural Networks 5 Parts Paper
Part 1)
Read the Case Study: Customer Segmentation Using K Means Clustering from Towards Data Science
https://towardsdatascience.com/customer-segmentation-using-k-means-clustering-d33964f238c3
Review the Code as well as the article:
https://github.com/abhinavsagar/kaggle-notebooks/blob/master/customer_segmentation.ipynb
Write 1-2 pages on the usefulness of Clustering.
Part 2)
Read the Case Study: Bayes’ rule with a simple and practical example from Towards Data Science
https://towardsdatascience.com/bayes-rule-with-a-simple-and-practical-example-2bce3d0f4ad0
Write 1-2 pages on the usefulness of Bayes Rule.
Part 3)
Research on your own a use for Neural Networks in the “real world” and provide the link to your source as well as a write up explaining the usefulness of the algorithm. This should also be about 1-2 pages.
Provide a link to your article/ case study that you found.
Use a Cover Page Following APA Formatting. What does that mean? See this link. See the example of a Cover Page.
https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/general_format.html
Provide a brief abstract for each section (what is the audience reading in your paper?) “This case study provides an example of ______. Then walk the reader through the mechanics of the paper – why are they using this algorithm and why is it useful. What is the outcome, etc. Make sure you include some sort of conclusion and perhaps a recommendation for how you would expand on the model – example: what else would you add to the model?
Part 4)
Run the 4 Notebooks for this week. The files are on the Wall.
After you run and review the output, create a Text Box at the bottom of file and tell me in your own words what the purpose of the algorithm is. Why its used and what the author was trying to solve.
Part 5)
Open this Colab file labeled Homework_2_MDE and run the code. Note, there are more efficient ways to run some of this, but I want you to focus on the output and answer the questions being asked.
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