Now that we have downloaded and validated the data, we can use it to create a dataset for our binary classification and regression model tasks. We want to be able to predict which customers will visit the shop in the next two weeks for the binary classification task, and how much they will spend in the next two weeks for the regression task. The Chapter4/prepare_data.R script transforms the raw transactional data into a format suitable for machine learning. You need to run the code to create the dataset for the models, but you do not have to understand exactly how it works. Feel free to skip ahead if you want to focus on the deep learning model building.
We need to transform our data into a suitable format ...
