The goal of this experiment is to build a Multi-Layer Perceptron (MLP), a Deep Neural Network (DNN) model, to predict the default of credit card clients.
Keywords: DNN, MLP, Supervised model, Prediction
We used the default of credit card clients dataset, a case of customers default payment in Taiwan, from UCI. It has 24 attributes (number of columns) and 30000 instances (number of rows).
You can find the modules and libraries used in this project in the requirement.txt file. You can also run the code below.
pip install -r requirements.txt
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Data: contains the data file used for this project.
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utils: contains the essential functions used for the data analysis.
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images: contains images generated in the experiment.
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models: contains the models generated in the experiment.
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Project_01.ipynb: a python notebook that shows the procedure of building, training, and evaluating the MLP model and the results got. It uses the functions in the utils to achieve this.
This project is licensed under the MIT License - see the LICENSE file for details.