Deep Bayesian Neural Networks for Prediction of Insurance Premiums
Abstract: In this project, the problem concerns predicting insurance premiums and particularly vehicle insurance premiums. These predictions were made with the help of Bayesian Neural Networks (BNNs), a type of Artificial Neural Network (ANN). The central concept of BNNs is that the parameters of the network follow distributions, which is beneficial. The modeling was done with the help of TensorFlow's Probability API, where a few models were built and tested on the data provided. The results conclude the possibility of predicting insurance premiums. However, the output distributions in this report were too wide to use. More data, both in volume and in the number of features, and better-structured data are needed. With better data, there is potential in building BNN and other machine learning (ML) models that could be useful for production purposes.
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