Summary

For the hackathon HSBC gave us 2gbs of text files containing data on their customer transaction records, products purchased, debt info, etc. Using this data I was to develop an algorithm that predicted if a new customer would purchase a HSBC prodcut within the next 3 months. A lot of this project was simply preparing the data to be able to put into a neural network because the data we were given was very unstructured and contained both numerical and categorical data. I made the categorical data points into one-hot vectors and then fed them along with the numerical data points into a simple perceptron algorithm which gave us very good results in loss and accuracy.

The Pre-processing required to get data in format where I could input it into the neural network

Graph of how training & validation loss fell and accuracy rose over the iterations