Prophet VS greykite

Compare Prophet vs greykite and see what are their differences.

Prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. (by facebook)

greykite

A flexible, intuitive and fast forecasting library (by linkedin)
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Prophet greykite
88 3
14,431 1,518
1.4% 2.0%
6.5 3.6
17 days ago 5 months ago
Python Python
MIT License BSD 2-clause "Simplified" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Prophet

Posts with mentions or reviews of Prophet. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-06.

greykite

Posts with mentions or reviews of greykite. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-19.

What are some alternatives?

When comparing Prophet and greykite you can also consider the following projects:

tensorflow - An Open Source Machine Learning Framework for Everyone

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

scikit-learn - scikit-learn: machine learning in Python

darts - A python library for easy manipulation and forecasting of time series.

MLflow - Open source platform for the machine learning lifecycle

sktime - A unified framework for machine learning with time series

Keras - Deep Learning for humans

pytorch-forecasting - Time series forecasting with PyTorch

Robyn - Robyn is an experimental, automated and open-sourced Marketing Mix Modeling (MMM) package from Facebook Marketing Science. It uses various machine learning techniques (Ridge regression with cross validation, multi-objective evolutionary algorithm for hyperparameter optimisation, gradient-based optimisation for budget allocation etc.) to define media channel efficiency and effectivity, explore adstock rates and saturation curves. It's built for granular datasets with many independent variables and therefore especially suitable for digital and direct response advertisers with rich dataset.

H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

SciKit-Learn Laboratory - SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.

Simple GAN - Attempt at implementation of a simple GAN using Keras