Our client is a financial institution who wants to use statistical methods and machine learning to improve their process. In this analysis, we aim at obtaining a model that may be used to determine if new applicants present a good or bad credit risk. To do this, we have at our disposal the German Credit data. A dataset on 1000 past credit applicants, described by 30 variables. Each applicant is rated as Good or Bad. The task is therefore learning from those past data to build model that would correctly rate the new clients.

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