data: https://drive.google.com/drive/folders/0B5_VOL6s8O6KWUd0dlI5OVRjYlk
progress: https://docs.google.com/document/d/19pQ7JyAXz3eZqGScN1xRQMPy_O5toEOogACMAC68Hkk/edit
description: https://docs.google.com/document/d/17dUl1nUFY0xhoZRMrhk3FI0uY5JJRTaIU-bs9tWob0c/edit
Kaggle: https://inclass.kaggle.com/c/dsg17-online-phase/

• Genre_id, media_id, album_id, user_id, artist_id -> aggregate (e.g. count)
• Ts_listen, release_date: date under 2 different formats -> put to same format
• Context_type -> one-hot-encode: 74 values from 0 to 73
• Platform_name, platform_family -> one-hot encode? Aggregate? (only 3 values each)
• Media_duration -> this one seems simple, keep as is
• Listen_type -> probably keep as is, but not sure
• User_gender -> keep as is (sexism!)
• User_age -> keep as is

• compute mean length for an album, an artist, a genre, mean of is_listened for each user, each artist, etc using the date
• Using the date, we can compute the number of songs he listened in a row

I think the key here is correctly using the information about artist, etc…

• XGBoost
• Neural Networks
• Reduce dimensions selecting only important features?
• Question: how to use the .json file?