[P] Momixa - Applying word embedding neural networks to playlist generation • r/MachineLearning

So the title should be pretty self descriptive for learning about the songs. We have a data set of playlists scraped from Spotify, with songs that appear above a certain threshold, and we train our network to learn embeddings just like word2vec, using playlists as sentences. To generate the playlist, we find points along the (euclidean) line between the normalized vectors of the two songs the user selects. We then find a small set of the closest (cosine distance) songs to each point on this line, and from that set identify the song with the minimal squared cosine distance from the two original songs. Some playlists work out well.