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  Published Paper Details:

  Paper Title

Music Recommender System

  Authors

  Sarfraz Ahmad,  Sagori Halder,  Tanfeez Ahmad,  Vishnu Singh

  Keywords

NumPy, Pandas, Python, Cosine Similarity, Machine Learning.

  Abstract


For building the music recommender system it requires very much information or data. So, it is retrieval task. In this project, we will be using a sample data set of songs to find the correlations between users and songs so that a new song will be recommended to them based on their previous history. We applied three approaches to build this music recommender system i.e., Popularity Based Filtering, Collaborative Filtering and Content Based Filtering. We will implement this project using libraries like NumPy, Pandas. We will also be using Cosine similarity along with Count Vectorizer. Along with this, a front end with flask that will show us the recommended songs when a specific song is processed.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2303926

  Paper ID - 233608

  Page Number(s) - h829-h834

  Pubished in - Volume 11 | Issue 3 | March 2023

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Sarfraz Ahmad,  Sagori Halder,  Tanfeez Ahmad,  Vishnu Singh,   "Music Recommender System", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 3, pp.h829-h834, March 2023, Available at :http://www.ijcrt.org/papers/IJCRT2303926.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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