Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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    http://www.apache.org/licenses/LICENSE-2.0

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This is the code for the team "DIKU-IR" in the Spotify sequential skip prediction challenge (https://www.crowdai.org/challenges/spotify-sequential-skip-prediction-challenge)

This project consists of two python files, and a small file which contains mapping needed for the prepocessing in the folder cat_dict.

data_preprocessing.py contains all the necessary code for processing the data.
The processing depends on a small dictionary in the folder cat_dict, which translates the categorical string variables to integers for later one hot encoding.

The file tf_network.py contains the implementation of our model, and the necessary code for both training the network, and running the trained model on a trained model.

THe data folder is uploaded to show the structure used for this project, and don't include any data to run on.