Use Data Analytics to Study Music Streaming Patterns
How do Spotify, YouTube and Netflix recommend just the right 'play next'? All you need to figure this out is an internet connect and MS Excel.
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Here’s What You Work On
About the Company
The Atal Incubation Center within CIE has been set up exclusively for startups that deploy tech innovation for social impact to help India achieve the Sustainable Development Goals (SDGs). As Indian researchers and innovators begin to expand the boundaries of science, Atal Incubation Center provides a platform where these ideas can be turned into sustainable business solutions.
Bridging the gap
Did you know that over 60,000 songs are uploaded to Spotify every day, Netflix has a library of over 50,000 titles, And, YouTube - the biggest content aggregator of them all - adds 500 hours of content to its platform every minute? In order to keep a user engaged, it is vital for streaming services to generate relevant recommendations based on user data. Without these recommendations, it might be almost impossible for a user to continue navigating the sheer volume of content available on these sites.
In this menternship, you will investigate the methods of data analytics utilized by music, video and podcast streaming services to generate recommendations, and use data from a music app to create a recommender system of your own.
Research reports on music recommender systems
Music recommender system for audio listeners
What you’ll need before starting
Any data analysis tool