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A project within the course Statistics for Data Science: Classifier for the danceability of songs based on 12 different song features derived from Spotify.

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JonnaMat/spotify-danceability-classifier

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Spotify Danceability Classifier

Project Description

The goal of this project is to build a classifier for the danceability of songs. Based on 12 different song features, such as acousticness, energy and liveness, we want to classify a song as danceable or not-danceable in order to be able to select the best songs for a party.

End-use cases

There are several end-use cases for this classifier. For example, as mentioned in the previous paragraph, a party organizer can use our classifier to create the perfect dance playlist. Another end-use case would be the production and creation of new songs. Current artists and producers can use the classifier to predict the party suitability of the song they are producing. any attributes of the classifier are song features that can be derived directly from the track [e.g., duration, loudness, time signature and mode]. Other features, like energy, speechiness, and valence, can be manually determined by the artist/ producers by applying their domain knowledge and expertise.

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A project within the course Statistics for Data Science: Classifier for the danceability of songs based on 12 different song features derived from Spotify.

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