Prophet
greykite
Prophet | greykite | |
---|---|---|
222 | 3 | |
17,893 | 1,797 | |
0.8% | 0.3% | |
7.0 | 4.8 | |
18 days ago | 5 months ago | |
Python | Python | |
MIT License | BSD 2-clause "Simplified" License |
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Prophet
- TimesFM (Time Series Foundation Model) for time-series forecasting
-
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."
- prophet: NEW Data - star count:17116.0
- prophet: NEW Data - star count:17082.0
- Facebook Prophet: library for generating forecasts from any time series data
- prophet: NEW Data - star count:16196.0
- prophet: NEW Data - star count:15889.0
greykite
-
Hello reddit, what time series forecasting tools are you using?
I've been using greykite for forecasting some business metrics lately.
- Darts: Non-Facebook alternative for timeseries forecasting
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Predicting Daily Sales
Some other options to potentially look into are Facebook's Prophet and one of my new favorites, Greykite. These have some very useful functions to automatically fit seasonality and holidays. They also have the flexibility allowing you to custom define holiday periods (think times when certain promotions or campaigns were running) and other regressors (think macroeconomic data that may have a material effect on your sales).
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.
sktime - A unified framework for machine learning with time series
scikit-learn - scikit-learn: machine learning in Python
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
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
MLflow - Open source platform for the machine learning lifecycle
Keras - Deep Learning for humans
pytorch-forecasting - Time series forecasting with PyTorch
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.