ch-ayesha / music-recommendation-system

Music-Recommendation-System

I have created Music Recommendation System using Spotify Dataset. To do this, I presented some of the visualization processes to understand data and done some EDA(Exploratory Data Analysis) so we can select features that are relevant to create a Recommendation System. This dataset contains the audio features for different songs along with the audio features for different genres. We can use this information to compare different genres and understand their unique differences in sound. Based on the analysis and visualizations, it’s clear that similar genres tend to have data points that are located close to each other while similar types of songs are also clustered together. This observation makes perfect sense. Similar genres will sound similar and will come from similar time periods while the same can be said for songs within those genres. We can use this idea to build a recommendation system by taking the data points of the songs a user has listened to and recommending songs corresponding to nearby data points. Spotipy is a Python client for the Spotify Web API that makes it easy for developers to fetch data and query Spotify’s catalog for songs. You have to install using pip install spotipy After installing Spotipy, you will need to create an app on the Spotify Developer’s page and save your Client ID and secret key. the idea behind is to extract meaningful keywords present in a song description a user likes, search for the keywords in other song descriptions to estimate similarities among them, and based on that, recommend those songs to the user.