song-reccomendation-based-on-user-schedule

This project shows an approach for a song reccomendation system based on user schedule

we first classify dataset of songs using classsification to create mood based song dataset

Then, we use clustering on activity dataset to add activities into mood map

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
.ipynb_checkpoints		.ipynb_checkpoints
ClassificationModel		ClassificationModel
__pycache__		__pycache__
submodels		submodels
ClusterinKmeans.ipynb		ClusterinKmeans.ipynb
README.md		README.md
activityData.csv		activityData.csv
activity_dataMaker.ipynb		activity_dataMaker.ipynb
chi_testing_parameters.ipynb		chi_testing_parameters.ipynb
data-download.ipynb		data-download.ipynb
heart_rate.csv		heart_rate.csv
playlist.ipynb		playlist.ipynb
report.csv		report.csv
reportOG.csv		reportOG.csv
reportOG1.csv		reportOG1.csv
smartwatch.csv		smartwatch.csv
temp.ipynb		temp.ipynb
usefulWatch.csv		usefulWatch.csv

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