H2O VS Prophet

Compare H2O vs Prophet and see what are their differences.

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. (by h2oai)

Prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. (by facebook)
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H2O Prophet
1 61
5,681 13,909
0.9% 1.2%
9.9 7.2
5 days ago 7 days ago
Jupyter Notebook Python
Apache License 2.0 MIT 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.

H2O

Posts with mentions or reviews of H2O. We have used some of these posts to build our list of alternatives and similar projects.
  • [PAID] Looking for Phaser.js game developer
    1 project | reddit.com/r/INAT | 9 Dec 2021
    Built and founded various web3 projects for last 2 years such as OpenArt and 8RealmDojo for last 2 years as well as being high performing student in CTU in Prague and SeoulTech. Was offered internships in Amazon and H2O.ai. Created robots assistants using robots from SoftBank.

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 2021-12-22.

What are some alternatives?

When comparing H2O and Prophet 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

greykite - A flexible, intuitive and fast forecasting library

MLflow - Open source platform for the machine learning lifecycle

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

Keras - Deep Learning for humans

sktime - A unified framework for machine learning with time series

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.