{"id":25441919,"url":"https://github.com/alpha597/music_classification_ml","last_synced_at":"2026-04-11T04:32:47.673Z","repository":{"id":277723200,"uuid":"933294549","full_name":"alpha597/Music_Classification_ML","owner":"alpha597","description":"A project which compares different machine learning algorithms' accuracy in music genre classification of a large dataset.","archived":false,"fork":false,"pushed_at":"2025-02-15T16:56:48.000Z","size":170,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-15T17:30:29.416Z","etag":null,"topics":["machine-learning","pandas","python","scikit-learn","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/alpha597.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-02-15T16:09:08.000Z","updated_at":"2025-02-15T16:56:51.000Z","dependencies_parsed_at":"2025-02-15T17:40:34.732Z","dependency_job_id":null,"html_url":"https://github.com/alpha597/Music_Classification_ML","commit_stats":null,"previous_names":["alpha597/music_classification_ml"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alpha597%2FMusic_Classification_ML","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alpha597%2FMusic_Classification_ML/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alpha597%2FMusic_Classification_ML/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alpha597%2FMusic_Classification_ML/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/alpha597","download_url":"https://codeload.github.com/alpha597/Music_Classification_ML/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239293947,"owners_count":19615043,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["machine-learning","pandas","python","scikit-learn","tensorflow"],"created_at":"2025-02-17T13:16:01.329Z","updated_at":"2025-12-30T21:49:27.911Z","avatar_url":"https://github.com/alpha597.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Music_Classification_ML\nClassify music dataset using Machine Learning algorithms using Tensorflow and Skicit-learn\n\nthis classification is done by several features of music- tempo, loudness, beats, pitch, root mean square error, spectral_centroid, zero_crossing rate etc.\nExtra features extracted from audio files, using librosa library of Python \nClassifying music into 10 generes - Classical , blues, rock, country, metal , pop, jazz etc. Each music genre has it's own feature combination and we  want to classify the dataset into 10 groups. At first we have used the Support Vector machine(SVM) algorithm both linear and rbf model\n\nCollected music dataset from  https://www.kaggle.com/datasets/insiyeah/musicfeatures/data\n\n\nbelow is accuracy of this model -confusion matrix\nSVM model accuracy - approx 60% \n\n![image](https://github.com/user-attachments/assets/562755c1-d755-471f-aef3-b078226e4608)\n\nnext algorithm to apply - KNN, K-Means Clustering, Neural networks... etc\nSVM performance can be increased using unsupervised learning PCA algorithm \n\n\nNext applied algorithm is KNN(K Nearest neighbours)\nHere accuracy increases to 65%\nbelow the new confusion maxtrix\n\n![image](https://github.com/user-attachments/assets/493c674b-68f5-4179-8e6f-7305271d5b7b)\n\nNext used model is KMeans Clustering, accuracy increases much more\nusing sklearn evaluation matrix\n![image](https://github.com/user-attachments/assets/86d232a1-f59f-46a1-85b6-0d8e8f248db5)\n\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falpha597%2Fmusic_classification_ml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falpha597%2Fmusic_classification_ml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falpha597%2Fmusic_classification_ml/lists"}