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Clustering clients of a German bank

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The ultimate goal of this project is to cluster the clients of a German bank, using the machine learning algorithm K-Means in order to provide the bank with important information about its clients and to try to answer the business question: "How should the bank personalise its investment products for its customers?".

The original dataset contains 1000 observations (people asking for a credit in a bank) with 10 variables for each person.

The project was developed entirely in the R language with detailed comments in the code

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