Experiments with (auto)scaling for the demo app on Raspberry Pi built for the vector-based retrieval system described in the post "Building Music Playlists Recommendation System."
Demo app built on Raspberry Pi for the sequence-to-sequence model described in the post "Building Music Playlists Recommendation System"
Documenting the lessons from redesigning search for our discovery system outlined in "Bit Of This, Bit Of That: Revisiting Search & Discovery"
Documenting the lessons from integrating vector databases into our discovery system outlined in "Bit Of This, Bit Of That: Revisiting Search & Discovery"
Documenting the lessons from transitioning to a microservices architecture in our discovery system outlined in "Bit Of This, Bit Of That: Revisiting Search & Discovery"
Documenting the lessons from our initial monolithic approach in our discovery system outlined in "Bit Of This, Bit Of That: Revisiting Search & Discovery"
Genre-based categorization forms a vital part of music discovery. What started several decades ago as just a way to market and segment artists into well-defined categories today forms the core of the user experience in music apps in the form of …
With an aim towards playlist discovery and recommendation, we leverage sequence-to-sequence modeling to learn a fixed-length representation of playlists in an unsupervised manner.
Content taken from our paper titled “Representation, Exploration, and Recommendation Of Music Playlists”
Building an app to analyze music preferences using Spotify API.