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As mentioned in the introduction, the actual proposal that you will be submitting should outline a problem that you want to solve and how you will use data mining techniques to solve it. A business problem from your work would be a likely candidate but it doesn't have to be directly related to your work. The key is that this should not be a hypothetical example like something from the textbook, it should be something with which you have personal experience.
The draft of your proposal should include:
1. A description of the problem you want to support with a data science solution.
2. Why the problem you selected can be solved with predictive modeling.
3. The use you want to support with this solution and how it could add value to an organization.
4. A description of the model and data mining techniques that will be used and why they are appropriate given the problem at hand. If doing supervised learning the targetvariable should be clear.
5. How and where you would get the data required to train your model. This should also include at least 5 attributes that would help your predictive modeling.
What price would you bid if you must win the project? What price would you bid if you want to maximize the expected value of the contribution from this contract?
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