際際滷shows by User: MahanHosseinzadeh / http://www.slideshare.net/images/logo.gif 際際滷shows by User: MahanHosseinzadeh / Tue, 16 Jul 2019 18:34:21 GMT 際際滷Share feed for 際際滷shows by User: MahanHosseinzadeh Prophet at Scale: Using Prophet at scale to tune and forecast time series at Spotify /slideshow/prophet-at-scale-using-prophet-at-scale-to-tune-and-forecast-time-series-at-spotify/155957937 prophetatscale-190716183421
Spotify has many time series to be forecasted such as streams forecast, monthly active users, ads inventory and consumption, etc. Prophet library has been very effective in capturing most of the time series requirements, however tuning is necessary as the default set of parameters don't perform well on our more noisy datasets with many confounding factors.]]>
Spotify has many time series to be forecasted such as streams forecast, monthly active users, ads inventory and consumption, etc. Prophet library has been very effective in capturing most of the time series requirements, however tuning is necessary as the default set of parameters don't perform well on our more noisy datasets with many confounding factors.]]> Tue, 16 Jul 2019 18:34:21 GMT /slideshow/prophet-at-scale-using-prophet-at-scale-to-tune-and-forecast-time-series-at-spotify/155957937 MahanHosseinzadeh@slideshare.net(MahanHosseinzadeh) Prophet at Scale: Using Prophet at scale to tune and forecast time series at Spotify MahanHosseinzadeh Spotify has many time series to be forecasted such as streams forecast, monthly active users, ads inventory and consumption, etc. Prophet library has been very effective in capturing most of the time series requirements, however tuning is necessary as the default set of parameters don't perform well on our more noisy datasets with many confounding factors. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/prophetatscale-190716183421-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Spotify has many time series to be forecasted such as streams forecast, monthly active users, ads inventory and consumption, etc. Prophet library has been very effective in capturing most of the time series requirements, however tuning is necessary as the default set of parameters don&#39;t perform well on our more noisy datasets with many confounding factors.
Prophet at Scale: Using Prophet at scale to tune and forecast time series at Spotify from Mahan Hosseinzadeh
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