4 Citations   Views   Downloads

Forecasting at scale

View preprint
9\ Last but not least, a very detailed paper on the Prophet model framework. https://t.co/QvlXEsJujp
@seanjtaylor & Benjamin Letham describe why & how @facebook’s #DataScience team developed #OpenSource Prophet to help analysts #forecast #timeseries at scale. @fbOpenSource https://t.co/BC8aByroRh https://t.co/DioUvGVF1l
35 days ago
RT @sagecodes: Day 2: Went to a @ps_python meetup discussing time series forecasting at scale with FB Prophet so I thought I would do an im…
35 days ago
RT @sagecodes: Day 2: Went to a @ps_python meetup discussing time series forecasting at scale with FB Prophet so I thought I would do an im…
35 days ago
RT @sagecodes: Day 2: Went to a @ps_python meetup discussing time series forecasting at scale with FB Prophet so I thought I would do an im…
Day 2: Went to a @ps_python meetup discussing time series forecasting at scale with FB Prophet so I thought I would do an implementation using it. Used it on a Chicago crime dataset. Read the paper here: https://t.co/EsR4FftfvI #100DaysOfCode #100DaysOfMLCode https://t.co/zVB1RTO1gM
52 days ago
Forecast meraklısı varsa, Facebook'un #Prophet 'inin whitepaperına göz atsın. https://t.co/ENFpTPDOAm
Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. https://t.co/TNb9yRK1Bx
@willyhakim @_bletham_ Thank you! Not sure when I'll have time for a more thorough write-up, but you can read our PeerJ paper, which is a decent explanation: https://t.co/5J02dNm6l5
154 days ago
RT @DuaneJRich: If you’d like to effectively tackle a forecasting problem quickly, check out Facebook’s prophet: https://t.co/CwCHNnCMWZ, p…
154 days ago
If you’d like to effectively tackle a forecasting problem quickly, check out Facebook’s prophet: https://t.co/CwCHNnCMWZ, paper here: https://t.co/ZtAmPTRgk7
@fbOpenSource Já ia me esquecendo. Aqui o paper: https://t.co/4PEqijb73f
Forecasting at scale https://t.co/8qScLHjHMn via @PeerJPreprints
RT @rvalyi: Probably useful for Odoo: prophet: tool for producing high quality forecasts for time series data that has multiple seasonality…
RT @rvalyi: Probably useful for Odoo: prophet: tool for producing high quality forecasts for time series data that has multiple seasonality…
RT @rvalyi: Probably useful for Odoo: prophet: tool for producing high quality forecasts for time series data that has multiple seasonality…
RT @rvalyi: Probably useful for Odoo: prophet: tool for producing high quality forecasts for time series data that has multiple seasonality…
260 days ago
Probably useful for Odoo: prophet: tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. https://t.co/cq0TJPEABN https://t.co/mXHiipQvdb
@mdrshhn @twiecki @NumFOCUS https://t.co/exMpFVa7MQ
Forecasting at Scale https://t.co/p2okpicdxR
Aquí el paper de Taylor @seanjtaylor y Letham https://t.co/fK5dCfR8RW Forecasting at Scale
Get the open-source software — Prophet: https://t.co/lKxllluTzy Read a preprint version: https://t.co/Nqv2krvn48
@dom_woodman @jroakes The prophet paper https://t.co/jggblry4t8 talks a bit about it but that isn't the main focus so prob better resources elsewhere. Basic idea is that if you already have a large market share then you can't grow that fast
Forecasting at scale prophet by Facebook https://t.co/sLHQKse2eC
Forecasting at scale https://t.co/PUlcUBtgM1 via @PeerJPreprints
NOT PEER-REVIEWED
"PeerJ Preprints" is a venue for early communication or feedback before peer review. Data may be preliminary.

Additional Information

Competing Interests

Sean J Taylor and Benjamin Letham are both employees at Facebook, Inc.

Author Contributions

Sean J Taylor analyzed the data, wrote the paper, prepared figures and/or tables, performed the computation work, reviewed drafts of the paper.

Benjamin Letham analyzed the data, wrote the paper, prepared figures and/or tables, performed the computation work, reviewed drafts of the paper.

Data Deposition

The following information was supplied regarding data availability:

All code is available in our open source repository: https://github.com/facebookincubator/prophet

Funding

The authors received no funding for this work.


Add your feedback

Before adding feedback, consider if it can be asked as a question instead, and if so then use the Question tab. Pointing out typos is fine, but authors are encouraged to accept only substantially helpful feedback.

Some Markdown syntax is allowed: _italic_ **bold** ^superscript^ ~subscript~ %%blockquote%% [link text](link URL)
 
By posting this you agree to PeerJ's commenting policies