Buyer non buyer prediction using deep learning.
The data we are working with is from audiobook app. Each record signifies each person who has purchased at least once.
We want to create a machine learning algorithm based on our data that can predict if a customer will buy again from the audio book company.
The main idea is that the company shouldn't spend its advertising budget targeting individuals who are unlikely to come back
Dataset folder contains detailed information about the features captured and assumptions
I have applied simple deep learning model with 2 hidden layers , adam optimizer , relu activation function and accuracy as the metrics.
With 100 epochs ran on batch size of 100 I was able to achieve more than 90% accuracy.