A multi-layer neural network model for predicting approval for personal bank loans.
The dataset for this project consists of labeled data. The target column is called 'Personal Loan' which is used to predict whether a customer gets approved for loan or not.
As it can be seen, the data consists of various important features in making the decision for loan approval. This project is more of an introduction to building a neural network model for predictive modeling. We will be using Tensorflow and Keras via Python for achieving these tasks.
The dataset is fetched from the kaggle.com website.
- pandas
- numpy
- matplotlib
- seaborn
- tensorflow
Classification Performance
F1 Score: 0.9217
Precision: 0.9636
Recall: 0.8833
Accuracy: 0.9820
Hence, this project concludes the loan approval prediction system, using artificial neural network, deciding whether a bank customer should be approved a loan or not.