Question: Submit an ethical use policy for your scenario solution model. The policy will describe any ethical considerations and risks associated with the scenario and the

Submit an ethical use policy for your scenario solution model. The policy will describe any ethical considerations and risks associated with the scenario and the use of the machine learning model solution. The policy should include guidelines for organizational use, distribution of the model, and the solution results.

a) How-To: Develop guidelines for the organization that outlines recommended techniques and steps for ensuring accuracy of the model in

reuse/alternative uses. Consider the entire practitioner cycle in your guidelines, including the steps that were already completed for you upfront. In other words, while you did not perform the beginning steps of the practitioner cycle, because the data was provided for you, make sure you specify these steps in your guidelines for your organization.

b) Ethical Considerations: Analyze the scenario you chose to attend to in your project and determine the potential ethical issues that could arise during any part of the practitioner cycle. What would you do to ensure that those following the guidelines that you developed stayed within ethical bounds? When and how could practitioners potentially go astray in following ethical standards throughout creation and use of a model? There are no right or wrong answers here, so you will not be graded on whether or not you are correct. Instead, you will be assessed on whether you have identified possible ethical concerns and whether you are able to suggest ways to keep practitioners in line with what you feel is ethical practice.

c) Ethical Use: What are the potential risks of unethical use of your results within your organization? What would you suggest to ensure that the results from your use of the model were used in an ethical manner? Explain your reasoning and concerns using examples.

Scenario

Case Study #2 Dataset name: Poker Hand Data Dataset location: https://archive.ics.uci.edu/ml/machine-learning-databases/poker/ Dataset attributes: 1025010 observables of 11 variables Dataset info: https://archive.ics.uci.edu/ml/datasets/Poker+Hand Problem: Predict poker hands

using a regression algorithms

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