Essays about: "Spotify"
Showing result 21 - 25 of 108 essays containing the word Spotify.
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21. Is Standardization Below the Standard? : A study of a highly standradized company adapting to the developing market of Kenya.
University essay from Mälardalens högskola/Akademin för ekonomi, samhälle och teknikAbstract : The goal of this study is to increase the knowledge surrounding the adaptation of highly standardized companies when it comes to entering developing markets from an already developed market. This study uses Spotify as an example when researching this topic. READ MORE
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22. Finding time-based listening habits in users music listening history to lower entropy in data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In a world where information, entertainment and e-commerce are growing rapidly in terms of volume and options, it can be challenging for individuals to find what they want. Search engines and recommendation systems have emerged as solutions, guiding the users. READ MORE
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23. A comparison of Data Stores for the Online Feature Store Component : A comparison between NDB and Aerospike
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis aimed to investigate what Data Stores would fit to be implemented as an Online Feature Store. This is a component in the Machine Learning infrastructure that needs to be able to handle low latency Reads at high throughput with high availability. READ MORE
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24. Recommend Songs With Data From Spotify Using Spectral Clustering
University essay from KTH/Skolan för teknikvetenskap (SCI)Abstract : Spotify, which is one of the worlds biggest music services, posted a data set and an open-ended challenge for music recommendation research. This study's goal is to recommend songs to playlists with the given data set from Spotify using Spectral clustering. READ MORE
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25. Categorization of songs using spectral clustering
University essay from KTH/Skolan för teknikvetenskap (SCI)Abstract : A direct consequence of the world becoming more digital is that the amount of available data grows, which presents great opportunities for organizations, researchers and institutions alike.However, this places a huge demand on efficient and understandable algorithms for analyzing vast datasets. READ MORE