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You are also expected to follow the principles we covered in the courses in preparing your presentation. Since you will obtain many results in your project, it is important for you to judiciously choose what to include in your presentation. In the last week, you are expected to present your analytics results to your clients. You will see that allocating funds wisely is crucial for the financial return of the investment portfolio.
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#How to use xlminer in excel for k clustering how to
Therefore, it is important for you to tune the different models in order to improve the performance.īeginning in the third week, we turn our attention to prescriptive analytics, where you will provide some concrete suggestions on how to allocate investment funds using analytics tools, including clustering and simulation based optimization.
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It is rarely the case that the default model produced by ASP is the best model possible. You will try a variety of tools and techniques this week, as the predictive accuracy of different tools can vary quite a bit. In the second week, you will perform some predictive analytics tasks, including classifying loans and predicting losses from defaulted loans. Needless to say, this step is crucial for the success of this project. As we discussed in this specialization, data preprocessing and cleanup is often the first step in data analytics projects. You will go through all typical steps of a data analytics project, including data understanding and cleanup, data analysis, and presentation of analytical results.įor the first week, the goal is to understand the data and prepare the data for analysis. In this capstone project, you will analyze the data on financial loans to help with the investment decisions of an investment company. The capstone project will take you from data to analysis and models, and ultimately to presentation of insights. The capstone of this specialization is designed with the goal of allowing you to experience this process. The analytics process is a collection of interrelated activities that lead to better decisions and to a higher business performance.