Who doesn't use Spotify nowadays to listen to their favorite music?
Sometimes you open it and search among its lists or recommendations for a song that you like to add it to your favorites. Well then, Today we are going to explain to you how some of these things that we see every day work in this app.
Spotify automatically learns about our tastes and preferences to recommend new songs to us by using various techniques and algorithms. Today we will talk about how you use Spotify Machine Learning to offer great service to the user.
Audio models
Spotify analyzes and reviews unprocessed audio tracks, that is, raw, in order to classify them within their categories.
This revision allows observe the similarities between the songs and therefore, recommend them to users based on their own history.
Natural Language Processing (NLP) Models
They analyze the metadata of each track and the blog posts and other publications written about that track or artist with NLP, then unify that data into a description of the particular track or artist. This tracking and data set is carried out daily, changing at all times to be as accurate as possible.
Collaborative filtration models
They analyze both the behavior of the user and others. Recommendations are made thanks to collaborative filtering. Spotify does not have a system by which users can “rate” their songs, failing which it uses implicit feedback; additional track counts and streaming data. Compare the songs listened to by users looking for those with similar musical tastes. By doing so, the Machine Learning From Spotify you get new common songs together and then get the ones that you individually haven't heard yet.
In this way, you can obtain information to recommend the songs among all users. The algorithms of this application end up offering a more than satisfactory service in which we, as end users, end up discovering our new favorite artist.
With the EIP International Business School you can access the world of advanced programming. Our Master in advanced programming in Python for Hacking, Big Data and Machine Learning It will train you to do specialized work in Python while you will be knowledgeable, inside, about tools such as Machine Learning.
