Machine learning and music: predicting the level of energy conveyed by a soundtrack
Colangelo, Roberto (A.A. 2022/2023) Machine learning and music: predicting the level of energy conveyed by a soundtrack. Tesi di Laurea in Data science in action, Luiss Guido Carli, relatore Giuseppe Francesco Italiano, pp. 85. [Master's Degree Thesis]
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Abstract/Index
Literature review. Data collection and columns description. Data exploration and visualization. Modeling. Tools and libraries. Data preparation and preprocessing. Metrics. Statistical learning and machine learning methods. Results comparison. Web application implementation.
References
Bibliografia: pp. 70-74.
Thesis Type: | Master's Degree Thesis |
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Institution: | Luiss Guido Carli |
Degree Program: | Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91) |
Chair: | Data science in action |
Thesis Supervisor: | Italiano, Giuseppe Francesco |
Thesis Co-Supervisor: | Sinaimeri, Blerina |
Academic Year: | 2022/2023 |
Session: | Summer |
Deposited by: | Alessandro Perfetti |
Date Deposited: | 09 Jan 2024 11:58 |
Last Modified: | 09 Jan 2024 11:58 |
URI: | https://tesi.luiss.it/id/eprint/37423 |
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