Use case – collaborative filtering

This use-case is about collaborative filtering. We are going to build a recommendation system based on embeddings created from a deep learning model. To do this, we are going to use the same dataset we used in Chapter 4, Training Deep Prediction Models, which is the retail transactional database. If you have not already downloaded the database, then go to the following link, https://www.dunnhumby.com/sourcefiles, and select Let’s Get Sort-of-Real. Select the option for the smallest dataset, titled All transactions for a randomly selected sample of 5,000 customers. Once you have read the terms and conditions and downloaded the dataset to your computer, unzip it into a directory called dunnhumby/in under the code folder. Ensure that the files are unzipped directly under this folder, and not a subdirectory, as you may have to copy...