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The latest from Primephonic

    Leveraging hidden co-occurrence relationships in classical music to develop an inexpensive recommender system

    Nowadays it’s pretty clear that to be successful, you need to incorporate data as part of your core business strategy, but getting the best out of your data is not always as simple as it sounds. You read about AI, machine learning, deep learning, big data, neural networks, etc., but what does this mean for a young startup?

    ( read )

    Topics: Streaming, data science, Machine learning

    Decomposing the composer landscape

    In the quest to compile and organise the most complete catalogue of classical music, we’ve encountered quite a few interesting insights into how the composer landscape has evolved over the years. In this article, we’ll take a deep dive into some of the findings we’ve acquired by doing what we love second most: data analysis (our first is classical music of course 🤓).

    ( read )

    Topics: Streaming, classical music, data science

    How do people listen to classical music?

    One of the downsides of the under-representation of classical music in existing streaming services, is that we have very limited exposure to datasets consisting purely of classical music usage. We’re only able to access data on an aggregate level, and since classical music streaming represents about 1% of the streaming market, any meaningful insights we could’ve gained from the peculiarities of classical music lovers, are quickly pushed to oblivion by the more popular genres.

    ( read )

    Topics: Streaming, classical music, data science