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Certificate of Completion
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THIS ACKNOWLEDGES THAT
HAS COMPLETED THE FALL 2023 DATA SCIENCE BOOT CAMP
Zachary Pollock
![clear.png](https://static.wixstatic.com/media/55f531_b9f3f13ce3aa4af78af2cc6d3563b81b~mv2.png/v1/fill/w_3,h_3,al_c,lg_1,q_85,enc_auto/clear.png)
Roman Holowinsky, PhD
DECEMBER 07, 2023
DIRECTOR
DATE
TEAM
GW Music Genre Classification
Aziz Burak Guelen, Afsin Ozdemir, Sacha L'Heveder, Jannatul Chhoa, Zachary Pollock, Ming Zhang
![clear.png](https://static.wixstatic.com/media/55f531_b9f3f13ce3aa4af78af2cc6d3563b81b~mv2.png/v1/fill/w_3,h_3,al_c,lg_1,q_85,enc_auto/clear.png)
Music is, in essence, a time series. We plan to develop an explainable model for classifying different music genres by using tools from optimal transport, namely, a variation of the Gromov-Wasserstein distance as described in the paper (Scalable Gromov–Wasserstein Based Comparison of Biological Time Series) https://doi.org/10.1007/s11538-023-01175-y.
Our goal is to make use of this GW distance in order to classify different music genres. We will also implement the algorithm from the paper.
![](https://static.wixstatic.com/media/a994932411404ef3bb797ba005125f5d.png/v1/fill/w_45,h_45,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/a994932411404ef3bb797ba005125f5d.png)
![](https://static.wixstatic.com/media/a994932411404ef3bb797ba005125f5d.png/v1/fill/w_45,h_45,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/a994932411404ef3bb797ba005125f5d.png)
![](https://static.wixstatic.com/media/a994932411404ef3bb797ba005125f5d.png/v1/fill/w_45,h_45,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/a994932411404ef3bb797ba005125f5d.png)
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