Prophet
pytorch-forecasting
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Prophet | pytorch-forecasting | |
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221 | 9 | |
17,652 | 3,533 | |
1.3% | - | |
6.7 | 8.7 | |
10 days ago | 7 days ago | |
Python | Python | |
MIT License | MIT License |
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Prophet
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Moirai: A Time Series Foundation Model for Universal Forecasting
https://facebook.github.io/prophet/
"Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well."
- Facebook Prophet: library for generating forecasts from any time series data
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Complete: D214 - MSDA Capstone
My rescue came from discovering some of the alternatives to ARIMA/SARIMA, which was the extent of what we had covered for time series data. A series of searches eventually led me to some automated time series analysis packages, one of which was Prophet, an open source time series package released by Facebook's core data science team. This was a life saver, being a much more efficient and more effective forecasting tool than sloooowly iterating through ARIMA/SARIMA models that seemed to want to fight with me. If you're going to do a time series analysis for your capstone, I strongly suggest taking a look at using Prophet.
- Dec 12, 2022 FLiP Stack Weekly
- Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
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[D] Time Series Question
Prophet
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LSTM/CNN architectures for time series forecasting[Discussion]
Prophet
- Eden
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Predição de ações na bolsa de valores com Python e Facebook Prophet
Prophet: Automação preditiva.
- Time series analysis of Bitcoin price in Python with fbprophet ?!
pytorch-forecasting
- FLaNK Stack Weekly for 14 Aug 2023
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LSTM/CNN architectures for time series forecasting[Discussion]
Pytorch-forecasting
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[P] Beware of false (FB-)Prophets: Introducing the fastest implementation of auto ARIMA [ever].
To name a few: https://github.com/jdb78/pytorch-forecasting, https://github.com/unit8co/darts, https://github.com/Nixtla/neuralforecast
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A python library for easy manipulation and forecasting of time series.
Darts is a pretty nice one. I've recently been using pytorch-forecasting for larger models like the Temporal Fusion Transformer. https://github.com/jdb78/pytorch-forecasting
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
darts - A python library for user-friendly forecasting and anomaly detection on time series.
scikit-learn - scikit-learn: machine learning in Python
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
greykite - A flexible, intuitive and fast forecasting library
MLflow - Open source platform for the machine learning lifecycle
Keras - Deep Learning for humans
sktime - A unified framework for machine learning with time series
neuralforecast - Scalable and user friendly neural :brain: forecasting algorithms.
Robyn - Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.
Lime-For-Time - Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification