As the musical industry is rapidly growing, there is an increasing demand for digital platforms for production and consumption of music. With this digitization, a lot of data regarding artists and tracks is available for analysis. Since music production is also digitized, methods for automating this process are emerging as well. The goal of this paper is to explore the methods of generation and popularity prediction. This will benefit , both the creators(music producers, music directors, arrangers, sound engineers) and also the business personnel (Artists and Repertoire, Record labels, artist managers, music distributors and streaming services). Music generation is the process of composing, and arranging melodies(composed of musical notes, within the restrictions of music theory). The popularity of a song depends on various factors such as hotness of the artist, tempo, scale, melody, emotion etc.
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